Tags
Amazon Mechanical Turk
Evaluation and User Preference Study on Spatial Diversity
by Tang and Sanderson (ECIR 2010) This article presents a user study which shows that users prefer search results which are not only (i) relevant but also (i...
BDM
Metrics for Evaluation of Ontology-based Information Extraction
by Maynard et al. This article describes metrics for evaluating ontologies. The article covers the following metrics: precision, recall False positives cost...
BI metrics
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
Big data
Rich Data, Poor Fields
This article shows how handheld devices and big data technology may multiply field yields and make farming more environmentally friendly.
Data Science and Prediction
by Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64—73. This article provides insights into how data science complem...
Hazy: Making It Easier to Build and Maintain Big-Data Analytics
Kumar, Arun, Feng Niu, and Christopher Ré. Hazy: Making It Easier to Build and Maintain Big-data Analytics. Communications of the ACM 56, no. 3...
CIMAWA
Using Word Association to Detect Multitopic Structures in Text Documents
Klahold, A. et al., 2014. Using Word Association to Detect Multitopic Structures in Text Documents. IEEE Intelligent Systems, 29(5), pp.40—46.</p&g...
ConceptNet
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
Crowdsourcing
Evaluation and User Preference Study on Spatial Diversity
by Tang and Sanderson (ECIR 2010) This article presents a user study which shows that users prefer search results which are not only (i) relevant but also (i...
Data Mining
Most Influential Data Mining Algorithms
As ranked by the IEEE International Conference on Data Mining2006 (ICDM 2006) C4.5 k-means support vector machines (SVM) Apriori expectation maximization (...
Evaluation Metrics
Spatial and Temporal Information
based on "Normalizing Spatial Information to Better Combine Criteria in Geographical Information Retrieval" y Palacio et al. (ECIR 2009). There are two types...
Forum
Using text mining and sentiment analysis for online forum hotspot detection
by Nan Li and Desheng Dash Wu (Decision Support Systems) The authors combine the following five features to detect forum hotspots using either (i) K-means cl...
Freebase
Combining Resources to Improve Unsupervised Sentiment Analysis at Aspect-Level
Jiménez-Zafra, S. M., Martín-Valdivia, M. T., Martínez-Cámara, E., & Ureña-López, L. A. (2016). Combining resources to improve unsupervised sentiment ana...
Geo
Spatial and Temporal Information
based on "Normalizing Spatial Information to Better Combine Criteria in Geographical Information Retrieval" y Palacio et al. (ECIR 2009). There are two types...
Grundlagen
Fortschritt in der Wirtschaftsinformatik
basierend auf Ideen aus dem Beitrag "Perspektiven der Wirtschaftsinformatik aus Sicht der Informatik" von Matthias Jarke Das relationale Datenmodell (Codd 19...
HITS algorithm
AGDISTIS - Graph-Based Disambiguation of Named Entities Using Linked Data
Summary This paper introduces a graph-based disambiguation approach for named entity linking that achieves higher F-measures than the state of the art and a ...
Hearst Pattern
Using a POS tagger for lexical knowledge acquisition
based on: Litz, Berenike, Langer, Hagen and Malaka, Rainer (2009). ''Trigrams'n'Tags for Lexical Knowledge Acquisition'', First International Conference on K...
Information Retrieval
Comparing the Sensitivity of Information Retrieval Metrics
by Radlinsky and Craswell (SIGIR 2010) This paper compares user behaviour based IR metrics with the following standard IR metrics: Precision@k -- the preci...
Ontology Building
Using Ontological Contexts to Assess the Relevance of Statements in Ontology Evolution
by Fouad Zablith, Mathieu d'Aquin, Marta Sabou, and Enrico Motta This work describes a method for judging the relevance statements suggested by ontology evol...
Ontology Evaluation
Using Ontological Contexts to Assess the Relevance of Statements in Ontology Evolution
by Fouad Zablith, Mathieu d'Aquin, Marta Sabou, and Enrico Motta This work describes a method for judging the relevance statements suggested by ontology evol...
On How to Perform a Gold Standard Based Evaluation of Ontology Learning
by K. Dellschaft and St. Staab This work provides an excellent overview of ontology evaluation measures, specifies criteria for good measures and introduces ...
PMI
Leveraging Sentiment Analysis for Topic Detection
by Cai et al (IBM China Research Lab) *** The authors combine sentiment detection with identifying the terms that are highly correlated to a specific sentime...
POS tagger
Using a POS tagger for lexical knowledge acquisition
based on: Litz, Berenike, Langer, Hagen and Malaka, Rainer (2009). ''Trigrams'n'Tags for Lexical Knowledge Acquisition'', First International Conference on K...
ProBase
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
Sentiment Detection
Ermittlung der Valenz von Nachrichten in Sozialen Netzen
Die Valenz (Sentiment; Semantic Orientation) eines Dokumentes definiert, ob dieses eine positive oder negative Polarität beziehungsweise Berichterstattung au...
Leveraging Sentiment Analysis for Topic Detection
by Cai et al (IBM China Research Lab) *** The authors combine sentiment detection with identifying the terms that are highly correlated to a specific sentime...
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melvile et al (IBM Watson Research Centre) ***** Analyzing blog posts raises a number of interesting questions: how to identify the subset of blogs discu...
Talks
KDIR causal knowledge
</p> Automatic identification of quasi-experimental designs for discovering causal knowledge by Jensen et. al</p> Introduction </p> blac...
TnT
Using a POS tagger for lexical knowledge acquisition
based on: Litz, Berenike, Langer, Hagen and Malaka, Rainer (2009). ''Trigrams'n'Tags for Lexical Knowledge Acquisition'', First International Conference on K...
WISE 2011
Word Sense Disambiguation for Automatic Taxonomy Construction from Text-Based Web Corpora
by de Knijff et al. This paper covers a framework that extracts terms from Web corpora, uses word sense disambiguation (WSD) to determine the word's senses,...
Web Intelligence
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
algorithms
It Probably Works
Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...
Hazy: Making It Easier to Build and Maintain Big-Data Analytics
Kumar, Arun, Feng Niu, and Christopher Ré. Hazy: Making It Easier to Build and Maintain Big-data Analytics. Communications of the ACM 56, no. 3...
application
Big, Linked Geospatial Data and Its Application in Earth Observation
Integrating earth observation data with linked open data would pave the way for easy reuse and integration of these datasets. The article discusses how knowl...
applications
Rich Data, Poor Fields
This article shows how handheld devices and big data technology may multiply field yields and make farming more environmentally friendly.
Model-Based Forecasting of Significant Societal Events
Ramakrishnan, Naren, Chang-Tien Lu, Madhav V. Marathe, Achla Marathe, Anil Vullikanti, Stephen Eubank, Scotland Leman, et al. Model-Based Forecasting of Sig...
The New Smart Cities
Mone, G. (2015). The New Smart Cities. Commun. ACM, 58(7), 20—21. http://doi.org/10.1145/2771297</p> </p> Summary This article discusses b...
The Power of Social Media Analytics
Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 74—81. doi:10.1145/2602574</p> Summa...
Healthcare Intelligence: Turing Data Into Knowledge
Yang, H., Kundakcioglu, E., Li, J., Wu, T., Mitchell, J. R., Hara, A., Tsui, K.-L. (2014). Healthcare Intelligence: Turning Data into Knowledge. IEEE Intell...
Big Data and Its Technical Challenges
Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big Data and Its Technical Chal...
Social Network Analysis and Mining for Business Applications
Bonchi, F., Castillo, C., Gionis, A., & Jaimes, A. (2011). Social Network Analysis and Mining for Business Applications. ACM Transactions on Intelligent ...
Management Support with Structured an Unstructured Data - An Integrated Business Intelligence Framework
Baars, Henning, and Hans-George Kemper. Management Support with Structured and Unstructured Data-An Integrated Business Intelligence Framework. Information...
Web Intelligence Applications
This article collects real world use cases of Web and Business Intelligence applications. Use Cases Business Intelligence: companies use their own data sourc...
A rule-based method for identifying the factor structure in customer satisfaction
Ahmad, A., Dey, L. & Halawani, S.M., 2012. A rule-based method for identifying the factor structure in customer satisfaction. Inf. Sci., 198, pp.118&mda...
architecture
An Overview of Business Intelligence Technology
Chaudhuri, S., Dayal, U. & Narasayya, V., 2011. An overview of business intelligence technology. Communications of the ACM, 54(8), pp.88—98. This a...
argument-based machine learning
Argument-based Machine Learning
Description Standard machine learning takes examples as input in the form of pairs (A, C), where A is an attribute value vector and C the class the example b...
artificial intelligence
Dynamic feature scaling for online learning of binary classifiers
This article describes and evaluates different online feature scaling approaches and their impact on the performance of binary classifiers. online feature...
aspect-based sentiment analysis
Combining Resources to Improve Unsupervised Sentiment Analysis at Aspect-Level
Jiménez-Zafra, S. M., Martín-Valdivia, M. T., Martínez-Cámara, E., & Ureña-López, L. A. (2016). Combining resources to improve unsupervised sentiment ana...
Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards
Thet, Tun Thura, Jin-Cheon Na, and Christopher S. G. Khoo. Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards. Journal of Information Scie...
average uninterpolated precision
Building and applying a concept hierarchy representation of a user profile
by Nanas et al. The focus on this paper is rather on the building of concept hierarchies and networks describing document repositories than on ontology evalu...
background knowledge
Combining Resources to Improve Unsupervised Sentiment Analysis at Aspect-Level
Jiménez-Zafra, S. M., Martín-Valdivia, M. T., Martínez-Cámara, E., & Ureña-López, L. A. (2016). Combining resources to improve unsupervised sentiment ana...
Open Information Extraction using Wikipedia
Wu, F. & Weld, D.S., 2010. Open information extraction using Wikipedia. In Proceedings of the 48th Annual Meeting of the Association for Computational Li...
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melvile et al (IBM Watson Research Centre) ***** Analyzing blog posts raises a number of interesting questions: how to identify the subset of blogs discu...
basics
Receiver Operating Characteristic Analysis - A Primer
Eng, J., 2005. Receiver Operating Characteristic Analysis: A Primer1. Academic Radiology, 12(7), pp.909—916. </p> Introduction </p> This ar...
big data
The Pathologies of Big data
by Jacobs, Adam (2009). The pathologies of big data, Communications of the ACM, ACM, pages 36-44, 52(8) The article demonstrates the importance of a profound...
bootstrapping
Automatische Ermittlung der Relevanz von Nachrichten
Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbest#nde und reichern...
bot detection
The DARPA Twitter Bot Challenge
Subrahmanian, V. S., A. Azaria, S. Durst, V. Kagan, A. Galstyan, K. Lerman, L. Zhu, E. Ferrara, A. Flammini, and F. Menczer. The DARPA Twitter Bot Challenge....
bots
The DARPA Twitter Bot Challenge
Subrahmanian, V. S., A. Azaria, S. Durst, V. Kagan, A. Galstyan, K. Lerman, L. Zhu, E. Ferrara, A. Flammini, and F. Menczer. The DARPA Twitter Bot Challenge....
brain storming
Extracting Concepts
This article collects some thoughts on normalizing phrases to concepts. Examples: drive_car <- "drive a car", "you drive your car", "driving cars" and "...
business intelligence
Management Support with Structured an Unstructured Data - An Integrated Business Intelligence Framework
Baars, Henning, and Hans-George Kemper. Management Support with Structured and Unstructured Data-An Integrated Business Intelligence Framework. Information...
An Overview of Business Intelligence Technology
Chaudhuri, S., Dayal, U. & Narasayya, V., 2011. An overview of business intelligence technology. Communications of the ACM, 54(8), pp.88—98. This a...
ACM Tech Pack on Business Intelligence and Data Management
Cupoli, P. et al., 2012. ACM Tech Pack on Business Intelligence/Data Management. ACM. Available at: http://techpack.acm.org/bi/. This tech pack contains a hi...
Web Intelligence Applications
This article collects real world use cases of Web and Business Intelligence applications. Use Cases Business Intelligence: companies use their own data sourc...
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
business metrics
Discovering company revenue relations from news: A network approach
Ma, Z., Sheng, O.R.L. & Pant, G., 2009. Discovering company revenue relations from news: A network approach. Decission Support Systems, 47(4), pp.408&mda...
Mining competitor relationships from online news: A network based approach
Ma, Z., Pant, G. & Sheng, O.R.L., 2011. Mining competitor relationships from online news: A network-based approach. Electronic Commerce Research and Appl...
categorization
Social Network Analysis and Mining for Business Applications
Bonchi, F., Castillo, C., Gionis, A., & Jaimes, A. (2011). Social Network Analysis and Mining for Business Applications. ACM Transactions on Intelligent ...
challenges
Healthcare Intelligence: Turing Data Into Knowledge
Yang, H., Kundakcioglu, E., Li, J., Wu, T., Mitchell, J. R., Hara, A., Tsui, K.-L. (2014). Healthcare Intelligence: Turning Data into Knowledge. IEEE Intell...
Big Data and Its Technical Challenges
Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big Data and Its Technical Chal...
classification
Dynamic feature scaling for online learning of binary classifiers
This article describes and evaluates different online feature scaling approaches and their impact on the performance of binary classifiers. online feature...
A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis
Cruz, Noa P., Maite Taboada, and Ruslan Mitkov. A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis. Journal of the As...
Receiver Operating Characteristic Analysis - A Primer
Eng, J., 2005. Receiver Operating Characteristic Analysis: A Primer1. Academic Radiology, 12(7), pp.909—916. </p> Introduction </p> This ar...
Mining competitor relationships from online news: A network based approach
Ma, Z., Pant, G. & Sheng, O.R.L., 2011. Mining competitor relationships from online news: A network-based approach. Electronic Commerce Research and Appl...
clique
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G. et al., 2005. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043), p.814. </p> Introd...
clique percolation method
Thematic Exploration of Linked Data
by Castano et al.; Very Large Data Search (VLDS) 2011 This article addresses the problem of organizing linked data, which features an inherent flat organizat...
clustering
Employment relations: a data driven analysis of job markets using online job boards and online professional networks
Career websites contain valuable data on employees, their skill sets and, employment history. This article uses k-means clustering on keywords describing ski...
Using Word Association to Detect Multitopic Structures in Text Documents
Klahold, A. et al., 2014. Using Word Association to Detect Multitopic Structures in Text Documents. IEEE Intelligent Systems, 29(5), pp.40—46.</p&g...
Thematic Exploration of Linked Data
by Castano et al.; Very Large Data Search (VLDS) 2011 This article addresses the problem of organizing linked data, which features an inherent flat organizat...
co-occurrence
Sentimantics: Lexical Sentiment Polarity Representations with Contextuality
Das, A. & Gambäck, B., 2012. Sentimantics: conceptual spaces for lexical sentiment polarity representation with contextuality. In Proceedi...
co-reference resolution
Automatic knowledge extraction from documents
Fan, J., Kalyanpur, A., Gondek, D. C., & Ferrucci, D. A. (2012). Automatic knowledge extraction from documents. IBM Journal of Research and Development, ...
common knowledge
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
common sense knowledge
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
Digital Intuition: Applying Common Sense Using Dimensionality Reduction
Havasi, C., Pustejovsky, J., Speer, R., & Lieberman, H. (2009). Digital Intuition: Applying Common Sense Using Dimensionality Reduction. Intelligent Syst...
comparative sentiment analysis
Techniques and applications for sentiment analysis
Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82—89. doi:10.1145/2436256.2436274 The articl...
components
An Overview of Business Intelligence Technology
Chaudhuri, S., Dayal, U. & Narasayya, V., 2011. An overview of business intelligence technology. Communications of the ACM, 54(8), pp.88—98. This a...
concept
Extracting Concepts
This article collects some thoughts on normalizing phrases to concepts. Examples: drive_car <- "drive a car", "you drive your car", "driving cars" and "...
Notions of Correctness when Evaluating Protein Name Taggers
by Olsson et al. This paper introduces six notions of correctness to evaluate the performance of protein name taggers: sloppy - which means that the propose...
concept tagging
Evaluating the Impact of Phrase Recognition on Concept Tagging
Mendes, P., Daiber, J., Rajapakse, R., Sasaki, F., & Bizer, C. (2012). Evaluating the Impact of Phrase Recognition on Concept Tagging. In Proceedings of...
concept-based sentiment analysis
Isanette: A Common and Common Sense Knowledge Base for Opinion Mining
Cambria, E. et al., 2011. Isanette: A Common and Common Sense Knowledge Base for Opinion Mining. In Data Mining Workshops (ICDMW), 2011 IEEE 11th Internation...
conference
WISE 2011 - Training a Named Entity Recognizer on the Web
by Urbansky et al. The authors distinguish between three approaches towards NER: use of hand-crafted rules (lexicons, rules) supervised machine learning, an...
constraints
Identifying Relations for Open Information Extraction
by Fader et al. This paper addresses two major shortcomings of state of the art open information extraction systems: uninformative extractions that omit cri...
container infrastructure
Borg, Omega and Kubernetes
Burns, B., Grant, B., Oppenheimer, D., Brewer, E., & Wilkes, J. (2016). Borg, Omega, and Kubernetes. Commun. ACM, 59(5), 50—57. https://doi.org/10...
content half-life time
Catching a Viral Video
Broxton, Tom, Yannet Interian, Jon Vaver, and Mirjam Wattenhofer. Catching a Viral Video. Journal of Intelligent Information Systems 40, no. 2 (April 1, 201...
content life cycle
Meme ranking to maximize post virality in microblogging platforms
Bonchi, F., Castillo, C., & Ienco, D. (2013). Meme ranking to maximize posts virality in microblogging platforms. Journal of Intelligent Information Syst...
Catching a Viral Video
Broxton, Tom, Yannet Interian, Jon Vaver, and Mirjam Wattenhofer. Catching a Viral Video. Journal of Intelligent Information Systems 40, no. 2 (April 1, 201...
content placement strategies
Meme ranking to maximize post virality in microblogging platforms
Bonchi, F., Castillo, C., & Ienco, D. (2013). Meme ranking to maximize posts virality in microblogging platforms. Journal of Intelligent Information Syst...
Catching a Viral Video
Broxton, Tom, Yannet Interian, Jon Vaver, and Mirjam Wattenhofer. Catching a Viral Video. Journal of Intelligent Information Systems 40, no. 2 (April 1, 201...
context
Sentimantics: Lexical Sentiment Polarity Representations with Contextuality
Das, A. & Gambäck, B., 2012. Sentimantics: conceptual spaces for lexical sentiment polarity representation with contextuality. In Proceedi...
contextualization
Sentimantics: Lexical Sentiment Polarity Representations with Contextuality
Das, A. & Gambäck, B., 2012. Sentimantics: conceptual spaces for lexical sentiment polarity representation with contextuality. In Proceedi...
corpora
IdentityRank: Named entity disambiguation in the news domain
Fernández, N. et al., 2012. IdentityRank: Named entity disambiguation in the news domain. Expert Systems with Applications, 39(10), pp.9207&mda...
Evaluation in Information Retrieval
Manning, C.D., Raghavan, P. & Schütze, H., 2008. Introduction to Information Retrieval 1st ed., Cambridge University Press. Chapter 8 - Evaluation in inf...
corpus
The Web is not a Person - An Analysis of the Performance of Named-Entity Recognition
Krovetz, R. et al. 2011. The web is not a person, Berners-Lee is not an organization, and African-Americans are not locations: an analysis of the performance...
corpus creation
Automatic Creation of a Reference Corpus for Political Opinion Mining in User-Generated Content
by Sarmento et al. (TSA 2009) This article presents an approach which applies manually-crafted lexico-syntactic patterns to collect highly opinionated commen...
creation
The viability of web-derived polarity lexicons
by Velikovich et al. (Google research) This paper describes an approach for semi-automatically generating sentiment lexicon from seed terms and a Web corpus...
criteria for evaluation measures
On How to Perform a Gold Standard Based Evaluation of Ontology Learning
by K. Dellschaft and St. Staab This work provides an excellent overview of ontology evaluation measures, specifies criteria for good measures and introduces ...
curation
Checking Facts
The Web and social media produce massive amounts of data at different levels of quality and trustworthiness. New research focuses on creating methods for che...
customer reviews
What makes a helpful online Review?
Mudambi and Schuff This article presents a model for the helpfulness of customer reviews which is verified based on Amazon reviews. The article is quite inte...
customer satisfaction
A rule-based method for identifying the factor structure in customer satisfaction
Ahmad, A., Dey, L. & Halawani, S.M., 2012. A rule-based method for identifying the factor structure in customer satisfaction. Inf. Sci., 198, pp.118&mda...
data integration
Digital Intuition: Applying Common Sense Using Dimensionality Reduction
Havasi, C., Pustejovsky, J., Speer, R., & Lieberman, H. (2009). Digital Intuition: Applying Common Sense Using Dimensionality Reduction. Intelligent Syst...
data loading
NoDB: Efficient Query Execution on Raw Data Files
Alagiannis, Ioannis, Renata Borovica, Miguel Branco, Stratos Idreos, and Anastasia Ailamaki. NoDB: Efficient Query Execution on Raw Data Files. In Proceedi...
data management
ACM Tech Pack on Business Intelligence and Data Management
Cupoli, P. et al., 2012. ACM Tech Pack on Business Intelligence/Data Management. ACM. Available at: http://techpack.acm.org/bi/. This tech pack contains a hi...
data mining
Data Mining for Web Intelligence
by Han and Chen-Chuan This article discusses data mining as key technology for bringing intelligence and direction to our Web interactions. At first they dis...
data science
Data Science and Prediction
by Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64—73. This article provides insights into how data science complem...
data structures
Suffix array
The suffix array is a memory-efficient alternative to the suffix tree which provides a sorted list of string indices indicating the string’s suffixes.
40 years of suffix trees
Suffix trees are used in text searching, indexing, statistics. This article describes the history, construction, current developments and applications of suf...
Data sketching
This article introduces three popular data structures that efficiently handle and summarize large data sets.
date extraction
Finding Text Reuse in the Web
by Michael Bendersky and W. Bruce Croft (WSDM'09) This article discusses an approach for finding three different kinds of text reuse in the web: verbatim co...
dbpedia
Improving Efficiency and Accuracy in Multilingual Entity Extraction
Daiber, J. et al., 2013. Improving Efficiency and Accuracy in Multilingual Entity Extraction. In Proceedings of the 9th International Conference on Semantic...
Evaluating the Impact of Phrase Recognition on Concept Tagging
Mendes, P., Daiber, J., Rajapakse, R., Sasaki, F., & Bizer, C. (2012). Evaluating the Impact of Phrase Recognition on Concept Tagging. In Proceedings of...
deceptive reviews
Distributional Footprints of Deceptive Product Reviews
by Song Feng, Longfei Xing, Anupam Gogar and Yejin Choi 2012 The authors of this paper argue that there are natural distributions of opinions in reviews for ...
deep learning
Growing Pains for Deep Learning
Edwards, C. (2015). Growing Pains for Deep Learning. Commun. ACM, 58(7), 14—16. http://doi.org/10.1145/2771283</p> Summary This article provides...
dependency parsing
Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards
Thet, Tun Thura, Jin-Cheon Na, and Christopher S. G. Khoo. Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards. Journal of Information Scie...
deployment
Borg, Omega and Kubernetes
Burns, B., Grant, B., Oppenheimer, D., Brewer, E., & Wilkes, J. (2016). Borg, Omega, and Kubernetes. Commun. ACM, 59(5), 50—57. https://doi.org/10...
devops
Borg, Omega and Kubernetes
Burns, B., Grant, B., Oppenheimer, D., Brewer, E., & Wilkes, J. (2016). Borg, Omega, and Kubernetes. Commun. ACM, 59(5), 50—57. https://doi.org/10...
diffusion
Finding and tracking subjects within an ongoing debate
by Rudy Prabowo and Mike Thelwall (prabowo2008) This article tracks subjects in postings and bulletins by identifying co-occurring terms which represent thes...
Learning influence probabilities in social networks
by Goyal et al. (goya2010) The article's authors learn influence models based on social graphs and an action log Based on the learned models they are able ...
Information flow modeling based on diffusion rate for prediction and ranking
by Song et al. (song2007) Song et al. investigate the information flow in a user network. They try to (i) predict where information flows and (ii) who will m...
discussion
KDIR Panel Discussion
The Information Butler (Andreas Dengel) Learn from best practices Recommends resources (similar to MISTRAL) Context Identification of context ¨(Eye-tra...
distant supervision
Collective Cross-Document Relation Extraction Without Labelled Data
Yao, L., Riedel, S. & McCallum, A., 2010. Collective cross-document relation extraction without labelled data. In Proceedings of the 2010 Conference on ...
docker
Borg, Omega and Kubernetes
Burns, B., Grant, B., Oppenheimer, D., Brewer, E., & Wilkes, J. (2016). Borg, Omega, and Kubernetes. Commun. ACM, 59(5), 50—57. https://doi.org/10...
domain consensurs
Domain relevance of terminology
based on Navigli, R. and Velardi, P. (2004). ''Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites'', Computational Linguistics, page...
domain relevance
Domain relevance of terminology
based on Navigli, R. and Velardi, P. (2004). ''Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites'', Computational Linguistics, page...
domain specificity
Automatische Ermittlung der Relevanz von Nachrichten
Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbest#nde und reichern...
domain specifity
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melvile et al (IBM Watson Research Centre) ***** Analyzing blog posts raises a number of interesting questions: how to identify the subset of blogs discu...
dremel
Dremel: Interactive Analysis of Web-Scale Datasets
by Melnik et al. in Proceedings of the 36th International Conference on Very Large Data Bases 2010 This paper covers Dremel, a scalable, interactive ad-hoc q...
e-government
Text-Mining the Voice of the People
Evangelopoulos, N., & Visinescu, L. (2012). Text-mining the voice of the people. Communications of the ACM, 55(2), 62. doi:10.1145/2076450.2076467 This a...
education
Data Science and Prediction
by Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64—73. This article provides insights into how data science complem...
emotional analysis
Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security
Chung, W., & Zeng, D. (2016). Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security. Journ...
emotional contagion
Experimental evidence of massive-scale emotional contagion through social networks
Kramer, A. D. I., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedi...
epistemology
Data Science and Prediction
by Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64—73. This article provides insights into how data science complem...
ethics
Experimental evidence of massive-scale emotional contagion through social networks
Kramer, A. D. I., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedi...
evaluation
Evaluation Without Ground Truth in Social Media Research
Zafarani, Reza, and Huan Liu. Evaluation Without Ground Truth in Social Media Research. Communcations of the ACM 58, no. 6 (May 2015): 54—60. doi:10.1...
Natural Language Processing for Health and Social Media
Abbasi, A. et al., 2014. Social Media Analytics for Smart Health. IEEE Intelligent Systems, 29(2), pp.60—80.</p> </p> Summary In this arti...
A Comparison of Knowledge Extraction Tools for the Semantic Web
Gangemi, A., 2013. A Comparison of Knowledge Extraction Tools for the Semantic Web. In P. Cimiano et al., eds. The Semantic Web: Semantics and Big Data. Lect...
Receiver Operating Characteristic Analysis - A Primer
Eng, J., 2005. Receiver Operating Characteristic Analysis: A Primer1. Academic Radiology, 12(7), pp.909—916. </p> Introduction </p> This ar...
Evaluating Entity Linking with Wikipedia
Hachey, B. et al., 2013. Evaluating Entity Linking with Wikipedia. Artificial Intelligence, 194, pp.130—150. This article compares the performance of t...
Evaluation in Information Retrieval
Manning, C.D., Raghavan, P. & Schütze, H., 2008. Introduction to Information Retrieval 1st ed., Cambridge University Press. Chapter 8 - Evaluation in inf...
Evaluation of Named Entity Recognition Systems
Monica Marrero et al. (2009) Evaluation of Named Entity Extraction Systems, Research In Computer Science, Vol. 41 (2009), pp. 47-58 This paper presents a num...
The Web is not a Person - An Analysis of the Performance of Named-Entity Recognition
Krovetz, R. et al. 2011. The web is not a person, Berners-Lee is not an organization, and African-Americans are not locations: an analysis of the performance...
Identifying Relations for Open Information Extraction
by Fader et al. This paper addresses two major shortcomings of state of the art open information extraction systems: uninformative extractions that omit cri...
Remarks on Ontology Learning and Evaluation
This post contains some random remarks on ontology learning and evaluation: terms versus concepts: concepts are formed by grouping terms with the same meani...
evaluation data
From Names to Entities using Thematic Context Distance
Pilz, A., & Paaß, G. (2011). From Names to Entities Using Thematic Context Distance. In Proceedings of the 20th ACM International Conference...
evaluation measure
On How to Perform a Gold Standard Based Evaluation of Ontology Learning
by K. Dellschaft and St. Staab This work provides an excellent overview of ontology evaluation measures, specifies criteria for good measures and introduces ...
experiment design
Evaluation Without Ground Truth in Social Media Research
Zafarani, Reza, and Huan Liu. Evaluation Without Ground Truth in Social Media Research. Communcations of the ACM 58, no. 6 (May 2015): 54—60. doi:10.1...
Data Warehousing and Analytics Infrastructure at Facebook
Thusoo, A. et al., 2010. Data warehousing and analytics infrastructure at facebook. In Proceedings of the 2010 ACM SIGMOD International Conference on Managem...
fact checking
Checking Facts
The Web and social media produce massive amounts of data at different levels of quality and trustworthiness. New research focuses on creating methods for che...
farming
Rich Data, Poor Fields
This article shows how handheld devices and big data technology may multiply field yields and make farming more environmentally friendly.
feature scaling
Dynamic feature scaling for online learning of binary classifiers
This article describes and evaluates different online feature scaling approaches and their impact on the performance of binary classifiers. online feature...
feature selection
A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis
Cruz, Noa P., Maite Taboada, and Ruslan Mitkov. A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis. Journal of the As...
Web Page Classification: Features and Algorithms
Qi, X. & Davison, B.D., 2009. Web page classification: Features and algorithms. ACM Comput. Surv., 41(2), pp.12:1—12:31. </p> </p> C...
features
The DARPA Twitter Bot Challenge
Subrahmanian, V. S., A. Azaria, S. Durst, V. Kagan, A. Galstyan, K. Lerman, L. Zhu, E. Ferrara, A. Flammini, and F. Menczer. The DARPA Twitter Bot Challenge....
HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language Text
Yosef, M. A., Bauer, S., Hoffart, J., Spaniol, M., & Weikum, G. (2013). HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language...
flameware detection
Online Discussion Participation Prediction Using Non-Negative Matrix Factorization
Fung, Y.-H., Li, C.-H., & Cheung, W. K. (2007). Online Discussion Participation Prediction Using Non-negative Matrix Factorization. In Proceedings of th...
framework
Management Support with Structured an Unstructured Data - An Integrated Business Intelligence Framework
Baars, Henning, and Hans-George Kemper. Management Support with Structured and Unstructured Data-An Integrated Business Intelligence Framework. Information...
future internet
The Pathologies of Big data
by Jacobs, Adam (2009). The pathologies of big data, Communications of the ACM, ACM, pages 36-44, 52(8) The article demonstrates the importance of a profound...
gazetteers
Detecting Geographic Locations from Web Resources
by Wang et al. (GIR 2005) The articles of the author distinguish between three different types of geographic locations the provider location (= source locat...
geo-tagger-evaluation
An empirical study of the effects of NLP components on Geographic IR performance
by Stokes et al. This article focuses on the impact of NLP components on the task of toponym resolution (TR) and geographic information retrieval (GIR) &l...
geo-tagging
Evaluation and User Preference Study on Spatial Diversity
by Tang and Sanderson (ECIR 2010) This article presents a user study which shows that users prefer search results which are not only (i) relevant but also (i...
Judging the spatial relevance of documents for GIR
by Clough and Joho (Advances in Information Retrieval 2006) This articles describes a pilot study which assesses both thematic and geographic relevance based...
Detecting Geographic Locations from Web Resources
by Wang et al. (GIR 2005) The articles of the author distinguish between three different types of geographic locations the provider location (= source locat...
geospatial
Big, Linked Geospatial Data and Its Application in Earth Observation
Integrating earth observation data with linked open data would pave the way for easy reuse and integration of these datasets. The article discusses how knowl...
german
Extraktion von Ternären Relationen aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und...
Extraktion von Named-Entities aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und r...
global context
Relation Extraction and the Influence of Automatic Named-Entity Recognition
Giuliano, C., Lavelli, A. & Romano, L., 2007. Relation extraction and the influence of automatic named-entity recognition. ACM Transactions on Speech an...
Large-scale Incremental Processing Using Distributed Transactions and Notifications
by Peng and Dabek This paper introduces Percolator and the corresponding processing pipeline called Caffeine, which are systems for incrementally processing ...
Dremel: Interactive Analysis of Web-Scale Datasets
by Melnik et al. in Proceedings of the 36th International Conference on Very Large Data Bases 2010 This paper covers Dremel, a scalable, interactive ad-hoc q...
grammar rules
Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards
Thet, Tun Thura, Jin-Cheon Na, and Christopher S. G. Khoo. Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards. Journal of Information Scie...
Techniques and applications for sentiment analysis
Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82—89. doi:10.1145/2436256.2436274 The articl...
graph-based disambiguation
AGDISTIS - Graph-Based Disambiguation of Named Entities Using Linked Data
Summary This paper introduces a graph-based disambiguation approach for named entity linking that achieves higher F-measures than the state of the art and a ...
graph-based models
Targeted disambiguation of ad-hoc, homogeneous sets of named entities
Wang, C., Chakrabarti, K., Cheng, T., & Chaudhuri, S. (2012). Targeted disambiguation of ad-hoc, homogeneous sets of named entities. In Proceedings of th...
health
Natural Language Processing for Health and Social Media
Abbasi, A. et al., 2014. Social Media Analytics for Smart Health. IEEE Intelligent Systems, 29(2), pp.60—80.</p> </p> Summary In this arti...
Social Media Analytics for Smart Health
Abbasi, A., Adjeroh, D., Dredze, M., Paul, M. J., Zahedi, F. M., Zhao, H., Ross, A. (2014). Social Media Analytics for Smart Health. IEEE Intelligent System...
healthcare intelligence
Healthcare Intelligence: Turing Data Into Knowledge
Yang, H., Kundakcioglu, E., Li, J., Wu, T., Mitchell, J. R., Hara, A., Tsui, K.-L. (2014). Healthcare Intelligence: Turning Data into Knowledge. IEEE Intell...
heuristics
Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards
Thet, Tun Thura, Jin-Cheon Na, and Christopher S. G. Khoo. Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards. Journal of Information Scie...
hierarchical classification
Web Page Classification: Features and Algorithms
Qi, X. & Davison, B.D., 2009. Web page classification: Features and algorithms. ACM Comput. Surv., 41(2), pp.12:1—12:31. </p> </p> C...
high number of parameters
Clash of the Contagions - Cooperation and Competition in Information Diffusion
by Seth A. Myers and Jure Leskovec, IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium Introduction The authors present a statistica...
hive
Data Warehousing and Analytics Infrastructure at Facebook
Thusoo, A. et al., 2010. Data warehousing and analytics infrastructure at facebook. In Proceedings of the 2010 ACM SIGMOD International Conference on Managem...
hotspot detection
Using text mining and sentiment analysis for online forum hotspot detection
by Nan Li and Desheng Dash Wu (Decision Support Systems) The authors combine the following five features to detect forum hotspots using either (i) K-means cl...
ikt
Automatische Ermittlung der Relevanz von Nachrichten
Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbest#nde und reichern...
Verarbeitung von natürlichsprachigen Texten aus Sozialen Netzen
Der Anteil von benutzergenerierten Inhalten hat sich mit der Weiterentwicklung des World Wide Webs zum Web 2.0 beziehungsweise Social Web stark erhöht. Zusät...
imbalanced data sets
A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis
Cruz, Noa P., Maite Taboada, and Ruslan Mitkov. A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis. Journal of the As...
Mining competitor relationships from online news: A network based approach
Ma, Z., Pant, G. & Sheng, O.R.L., 2011. Mining competitor relationships from online news: A network-based approach. Electronic Commerce Research and Appl...
impact
Targeting Online Communities to Maximise Information Diffusion
Belák, V., Lam, S. & Hayes, C., 2012. Targeting online communities to maximise information diffusion. In Proceedings of the 21st internati...
implicit network connections
Social Network Analysis and Mining for Business Applications
Bonchi, F., Castillo, C., Gionis, A., & Jaimes, A. (2011). Social Network Analysis and Mining for Business Applications. ACM Transactions on Intelligent ...
importance
Social influence analysis in large-scale networks
by Tang et al. (tang2009), SIGKDD Tang et al. (2009) propose Topical Affinity Propagation (TAP) for determining the topic-level social influence of nodes in ...
incremental processing
Large-scale Incremental Processing Using Distributed Transactions and Notifications
by Peng and Dabek This paper introduces Percolator and the corresponding processing pipeline called Caffeine, which are systems for incrementally processing ...
influence
Extracting influential nodes on a social network for information diffusion
by Kimura, M. et al. (Data Mining and Knowledge Discovery 2010; kimura2010) This paper cover the optimization problem of finding the most influential nodes o...
Social influence analysis in large-scale networks
by Tang et al. (tang2009), SIGKDD Tang et al. (2009) propose Topical Affinity Propagation (TAP) for determining the topic-level social influence of nodes in ...
influence bots
The DARPA Twitter Bot Challenge
Subrahmanian, V. S., A. Azaria, S. Durst, V. Kagan, A. Galstyan, K. Lerman, L. Zhu, E. Ferrara, A. Flammini, and F. Menczer. The DARPA Twitter Bot Challenge....
information diffusion
Catching a Viral Video
Broxton, Tom, Yannet Interian, Jon Vaver, and Mirjam Wattenhofer. Catching a Viral Video. Journal of Intelligent Information Systems 40, no. 2 (April 1, 201...
Clash of the Contagions - Cooperation and Competition in Information Diffusion
by Seth A. Myers and Jure Leskovec, IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium Introduction The authors present a statistica...
Targeting Online Communities to Maximise Information Diffusion
Belák, V., Lam, S. & Hayes, C., 2012. Targeting online communities to maximise information diffusion. In Proceedings of the 21st internati...
Inferring networks of diffusion and influence
by Gomez Rodriguez, M.; Leskovec, J. & Krause, A. In order to study network diffusion, we need to identify the contagion (idea, information, virus, phra...
Finding and tracking subjects within an ongoing debate
by Rudy Prabowo and Mike Thelwall (prabowo2008) This article tracks subjects in postings and bulletins by identifying co-occurring terms which represent thes...
Learning influence probabilities in social networks
by Goyal et al. (goya2010) The article's authors learn influence models based on social graphs and an action log Based on the learned models they are able ...
Information flow modeling based on diffusion rate for prediction and ranking
by Song et al. (song2007) Song et al. investigate the information flow in a user network. They try to (i) predict where information flows and (ii) who will m...
information extraction
Mining competitor relationships from online news: A network based approach
Ma, Z., Pant, G. & Sheng, O.R.L., 2011. Mining competitor relationships from online news: A network-based approach. Electronic Commerce Research and Appl...
Extraktion von Ternären Relationen aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und...
Redundancy-based information extraction
The notion of redundancy-based information extraction utilizes the fact that many information on the Web is redundand, which leads to the consequences that ...
information processing
Distributed Information Processing in Biological and Computational systems
Navlakha, S. & Bar-Joseph, Z., 2014. Distributed information processing in biological and computational systems. Communications of the ACM, 58(1), pp.94...
information spaces
Data Mining for Web Intelligence
by Han and Chen-Chuan This article discusses data mining as key technology for bringing intelligence and direction to our Web interactions. At first they dis...
interpretation
Big Data and Its Technical Challenges
Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big Data and Its Technical Chal...
kdir2008
KDIR causal knowledge
</p> Automatic identification of quasi-experimental designs for discovering causal knowledge by Jensen et. al</p> Introduction </p> blac...
kdir2009
KDIR Panel Discussion
The Information Butler (Andreas Dengel) Learn from best practices Recommends resources (similar to MISTRAL) Context Identification of context ¨(Eye-tra...
keyword analysis
Evaluating the Impact of Phrase Recognition on Concept Tagging
Mendes, P., Daiber, J., Rajapakse, R., Sasaki, F., & Bizer, C. (2012). Evaluating the Impact of Phrase Recognition on Concept Tagging. In Proceedings of...
keyword extraction
Using Word Association to Detect Multitopic Structures in Text Documents
Klahold, A. et al., 2014. Using Word Association to Detect Multitopic Structures in Text Documents. IEEE Intelligent Systems, 29(5), pp.40—46.</p&g...
knowledge extraction
Automatic knowledge extraction from documents
Fan, J., Kalyanpur, A., Gondek, D. C., & Ferrucci, D. A. (2012). Automatic knowledge extraction from documents. IBM Journal of Research and Development, ...
language resources
The Web is not a Person - An Analysis of the Performance of Named-Entity Recognition
Krovetz, R. et al. 2011. The web is not a person, Berners-Lee is not an organization, and African-Americans are not locations: an analysis of the performance...
latent dirichlet allocation
Employment relations: a data driven analysis of job markets using online job boards and online professional networks
Career websites contain valuable data on employees, their skill sets and, employment history. This article uses k-means clustering on keywords describing ski...
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
From Names to Entities using Thematic Context Distance
Pilz, A., & Paaß, G. (2011). From Names to Entities Using Thematic Context Distance. In Proceedings of the 20th ACM International Conference...
latent semantic analysis
Digital Intuition: Applying Common Sense Using Dimensionality Reduction
Havasi, C., Pustejovsky, J., Speer, R., & Lieberman, H. (2009). Digital Intuition: Applying Common Sense Using Dimensionality Reduction. Intelligent Syst...
lexico-syntactic patterns
Automatic Creation of a Reference Corpus for Political Opinion Mining in User-Generated Content
by Sarmento et al. (TSA 2009) This article presents an approach which applies manually-crafted lexico-syntactic patterns to collect highly opinionated commen...
lexicon expansion
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
lexicons
Opinion Holder and Target Extraction for Verb-based Opinion Predicates - The Problem is Not Solved
Michael Wiegand, Marc Schulder, & Josef Ruppenhofer. (n.d.). Opinion Holder and Target Extraction for Verb-based Opinion Predicates -- The Problem is No...
lidstone smoothing
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melville et al. (KDD 2009) Motivation: </p> before the rise of the Web 2.0 companies published product information and reviews on Web sites ...
linear discriminant analysis
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
linked open data
Big, Linked Geospatial Data and Its Application in Earth Observation
Integrating earth observation data with linked open data would pave the way for easy reuse and integration of these datasets. The article discusses how knowl...
Combining Resources to Improve Unsupervised Sentiment Analysis at Aspect-Level
Jiménez-Zafra, S. M., Martín-Valdivia, M. T., Martínez-Cámara, E., & Ureña-López, L. A. (2016). Combining resources to improve unsupervised sentiment ana...
AGDISTIS - Graph-Based Disambiguation of Named Entities Using Linked Data
Summary This paper introduces a graph-based disambiguation approach for named entity linking that achieves higher F-measures than the state of the art and a ...
Automatic Semantic Web Annotation of Named Entities
Charton, E., Gagnon, M., & Ozell, B. (2011). Automatic semantic web annotation of named entities. In Proceedings of the 24th Canadian conference on Adva...
Sentimantics: Lexical Sentiment Polarity Representations with Contextuality
Das, A. & Gambäck, B., 2012. Sentimantics: conceptual spaces for lexical sentiment polarity representation with contextuality. In Proceedi...
Thematic Exploration of Linked Data
by Castano et al.; Very Large Data Search (VLDS) 2011 This article addresses the problem of organizing linked data, which features an inherent flat organizat...
linking open data
Digital Intuition: Applying Common Sense Using Dimensionality Reduction
Havasi, C., Pustejovsky, J., Speer, R., & Lieberman, H. (2009). Digital Intuition: Applying Common Sense Using Dimensionality Reduction. Intelligent Syst...
Isanette: A Common and Common Sense Knowledge Base for Opinion Mining
Cambria, E. et al., 2011. Isanette: A Common and Common Sense Knowledge Base for Opinion Mining. In Data Mining Workshops (ICDMW), 2011 IEEE 11th Internation...
local context
Relation Extraction and the Influence of Automatic Named-Entity Recognition
Giuliano, C., Lavelli, A. & Romano, L., 2007. Relation extraction and the influence of automatic named-entity recognition. ACM Transactions on Speech an...
locality sensitive hashing
It Probably Works
Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...
locality sensitve hashing
Near-optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
Andoni, A. & Indyk, P., 2008. Near-optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions. Communications of the ACM, 51(1), pp....
An Open Digest-based Technique for Spam Detection
Damiani, E. et al., 2004. An Open Digest-based Technique for Spam Detection. In in Proceedings of the 2004 International Workshop on Security in Parallel ...
lsa
Text-Mining the Voice of the People
Evangelopoulos, N., & Visinescu, L. (2012). Text-mining the voice of the people. Communications of the ACM, 55(2), 62. doi:10.1145/2076450.2076467 This a...
lsh
It Probably Works
Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...
Near-optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions
Andoni, A. & Indyk, P., 2008. Near-optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions. Communications of the ACM, 51(1), pp....
An Open Digest-based Technique for Spam Detection
Damiani, E. et al., 2004. An Open Digest-based Technique for Spam Detection. In in Proceedings of the 2004 International Workshop on Security in Parallel ...
machine learning
Dynamic feature scaling for online learning of binary classifiers
This article describes and evaluates different online feature scaling approaches and their impact on the performance of binary classifiers. online feature...
Argument-based Machine Learning
Description Standard machine learning takes examples as input in the form of pairs (A, C), where A is an attribute value vector and C the class the example b...
management support
Envisioning Intelligent Information Technologies through the Prism of Web Intelligence
Zhong et al. (Communications of the ACM) - coined the term Web Intelligence (see literature) This article introduces intelligent Information Technology (iIT)...
map reduce
Large-scale Incremental Processing Using Distributed Transactions and Notifications
by Peng and Dabek This paper introduces Percolator and the corresponding processing pipeline called Caffeine, which are systems for incrementally processing ...
Dremel: Interactive Analysis of Web-Scale Datasets
by Melnik et al. in Proceedings of the 36th International Conference on Very Large Data Bases 2010 This paper covers Dremel, a scalable, interactive ad-hoc q...
market predictors
Predicting the Future with Social Media
by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...
market research
A rule-based method for identifying the factor structure in customer satisfaction
Ahmad, A., Dey, L. & Halawani, S.M., 2012. A rule-based method for identifying the factor structure in customer satisfaction. Inf. Sci., 198, pp.118&mda...
matrix
IdentityRank: Named entity disambiguation in the news domain
Fernández, N. et al., 2012. IdentityRank: Named entity disambiguation in the news domain. Expert Systems with Applications, 39(10), pp.9207&mda...
method
Taking Refuge in Your Personal Sentic Corner
Cambria, E., Hussain, A. & Eckl, C., 2011. Taking Refuge in Your Personal Sentic Corner. In Proceedings of the Workshop on Sentiment Analysis where AI me...
methods
Most Influential Data Mining Algorithms
As ranked by the IEEE International Conference on Data Mining2006 (ICDM 2006) C4.5 k-means support vector machines (SVM) Apriori expectation maximization (...
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
metrics
Evaluating Entity Linking with Wikipedia
Hachey, B. et al., 2013. Evaluating Entity Linking with Wikipedia. Artificial Intelligence, 194, pp.130—150. This article compares the performance of t...
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
Evaluation in Information Retrieval
Manning, C.D., Raghavan, P. & Schütze, H., 2008. Introduction to Information Retrieval 1st ed., Cambridge University Press. Chapter 8 - Evaluation in inf...
Comparing the Sensitivity of Information Retrieval Metrics
by Radlinsky and Craswell (SIGIR 2010) This paper compares user behaviour based IR metrics with the following standard IR metrics: Precision@k -- the preci...
micro blogging
Ermittlung der Valenz von Nachrichten in Sozialen Netzen
Die Valenz (Sentiment; Semantic Orientation) eines Dokumentes definiert, ob dieses eine positive oder negative Polarität beziehungsweise Berichterstattung au...
misq
What makes a helpful online Review?
Mudambi and Schuff This article presents a model for the helpfulness of customer reviews which is verified based on Amazon reviews. The article is quite inte...
model
The Power of Social Media Analytics
Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 74—81. doi:10.1145/2602574</p> Summa...
model fitting
Clash of the Contagions - Cooperation and Competition in Information Diffusion
by Seth A. Myers and Jure Leskovec, IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium Introduction The authors present a statistica...
mtp
Using Word Association to Detect Multitopic Structures in Text Documents
Klahold, A. et al., 2014. Using Word Association to Detect Multitopic Structures in Text Documents. IEEE Intelligent Systems, 29(5), pp.40—46.</p&g...
multi-dimensional scaling
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
multitopic detection
Using Word Association to Detect Multitopic Structures in Text Documents
Klahold, A. et al., 2014. Using Word Association to Detect Multitopic Structures in Text Documents. IEEE Intelligent Systems, 29(5), pp.40—46.</p&g...
naive bayes
Clash of the Contagions - Cooperation and Competition in Information Diffusion
by Seth A. Myers and Jure Leskovec, IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium Introduction The authors present a statistica...
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melville et al. (KDD 2009) Motivation: </p> before the rise of the Web 2.0 companies published product information and reviews on Web sites ...
named entity disambiguation
From Names to Entities using Thematic Context Distance
Pilz, A., & Paaß, G. (2011). From Names to Entities Using Thematic Context Distance. In Proceedings of the 20th ACM International Conference...
named entity linking
AGDISTIS - Graph-Based Disambiguation of Named Entities Using Linked Data
Summary This paper introduces a graph-based disambiguation approach for named entity linking that achieves higher F-measures than the state of the art and a ...
HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language Text
Yosef, M. A., Bauer, S., Hoffart, J., Spaniol, M., & Weikum, G. (2013). HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language...
From Names to Entities using Thematic Context Distance
Pilz, A., & Paaß, G. (2011). From Names to Entities Using Thematic Context Distance. In Proceedings of the 20th ACM International Conference...
Improving Efficiency and Accuracy in Multilingual Entity Extraction
Daiber, J. et al., 2013. Improving Efficiency and Accuracy in Multilingual Entity Extraction. In Proceedings of the 9th International Conference on Semantic...
Evaluating the Impact of Phrase Recognition on Concept Tagging
Mendes, P., Daiber, J., Rajapakse, R., Sasaki, F., & Bizer, C. (2012). Evaluating the Impact of Phrase Recognition on Concept Tagging. In Proceedings of...
Targeted disambiguation of ad-hoc, homogeneous sets of named entities
Wang, C., Chakrabarti, K., Cheng, T., & Chaudhuri, S. (2012). Targeted disambiguation of ad-hoc, homogeneous sets of named entities. In Proceedings of th...
Automatic Semantic Web Annotation of Named Entities
Charton, E., Gagnon, M., & Ozell, B. (2011). Automatic semantic web annotation of named entities. In Proceedings of the 24th Canadian conference on Adva...
A Comparison of Knowledge Extraction Tools for the Semantic Web
Gangemi, A., 2013. A Comparison of Knowledge Extraction Tools for the Semantic Web. In P. Cimiano et al., eds. The Semantic Web: Semantics and Big Data. Lect...
Evaluating Entity Linking with Wikipedia
Hachey, B. et al., 2013. Evaluating Entity Linking with Wikipedia. Artificial Intelligence, 194, pp.130—150. This article compares the performance of t...
IdentityRank: Named entity disambiguation in the news domain
Fernández, N. et al., 2012. IdentityRank: Named entity disambiguation in the news domain. Expert Systems with Applications, 39(10), pp.9207&mda...
Evaluation of Named Entity Recognition Systems
Monica Marrero et al. (2009) Evaluation of Named Entity Extraction Systems, Research In Computer Science, Vol. 41 (2009), pp. 47-58 This paper presents a num...
Extraktion von Named-Entities aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und r...
named entity recognition
A Comparison of Knowledge Extraction Tools for the Semantic Web
Gangemi, A., 2013. A Comparison of Knowledge Extraction Tools for the Semantic Web. In P. Cimiano et al., eds. The Semantic Web: Semantics and Big Data. Lect...
A Survey of Types of Text Noise and Techniques to Handle Noisy Text
by Subramaniam, L. V., Roy, S., Faruquie, T. A., & Negi, S. (2009). A survey of types of text noise and techniques to handle noisy text. Proceedings of T...
WISE 2011 - Training a Named Entity Recognizer on the Web
by Urbansky et al. The authors distinguish between three approaches towards NER: use of hand-crafted rules (lexicons, rules) supervised machine learning, an...
Evaluation of Named Entity Recognition Systems
Monica Marrero et al. (2009) Evaluation of Named Entity Extraction Systems, Research In Computer Science, Vol. 41 (2009), pp. 47-58 This paper presents a num...
The Web is not a Person - An Analysis of the Performance of Named-Entity Recognition
Krovetz, R. et al. 2011. The web is not a person, Berners-Lee is not an organization, and African-Americans are not locations: an analysis of the performance...
Extraktion von Named-Entities aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und r...
named entity recogniton
HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language Text
Yosef, M. A., Bauer, S., Hoffart, J., Spaniol, M., & Weikum, G. (2013). HYENA-live: Fine-Grained Online Entity Type Classification from Natural-language...
named entity resolution
Improving Efficiency and Accuracy in Multilingual Entity Extraction
Daiber, J. et al., 2013. Improving Efficiency and Accuracy in Multilingual Entity Extraction. In Proceedings of the 9th International Conference on Semantic...
negation
Polarity Shift Detection, Elimination and Ensemble: A Three-Stage Model for Document-Level Sentiment Analysis
Xia, Rui, Feng Xu, Jianfei Yu, Yong Qi, and Erik Cambria. Polarity Shift Detection, Elimination and Ensemble: A Three-Stage Model for Document-Level Sentime...
A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis
Cruz, Noa P., Maite Taboada, and Ruslan Mitkov. A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis. Journal of the As...
What’s Great and What’s Not: Learning to Classify the Scope of Negation for Improved Sentiment Analysis
by Councill et. al - Proceedings of the Workshop on Negation and Speculation in NLP (July, 2010) </p> This paper uses conditional random fields to dete...
network
Sentimantics: Lexical Sentiment Polarity Representations with Contextuality
Das, A. & Gambäck, B., 2012. Sentimantics: conceptual spaces for lexical sentiment polarity representation with contextuality. In Proceedi...
network inferrence
Inferring networks of diffusion and influence
by Gomez Rodriguez, M.; Leskovec, J. & Krause, A. In order to study network diffusion, we need to identify the contagion (idea, information, virus, phra...
networks
Discovering company revenue relations from news: A network approach
Ma, Z., Sheng, O.R.L. & Pant, G., 2009. Discovering company revenue relations from news: A network approach. Decission Support Systems, 47(4), pp.408&mda...
Mining competitor relationships from online news: A network based approach
Ma, Z., Pant, G. & Sheng, O.R.L., 2011. Mining competitor relationships from online news: A network-based approach. Electronic Commerce Research and Appl...
neural network
Growing Pains for Deep Learning
Edwards, C. (2015). Growing Pains for Deep Learning. Commun. ACM, 58(7), 14—16. http://doi.org/10.1145/2771283</p> Summary This article provides...
nilsimsa
An Open Digest-based Technique for Spam Detection
Damiani, E. et al., 2004. An Open Digest-based Technique for Spam Detection. In in Proceedings of the 2004 International Workshop on Security in Parallel ...
nlp
Natural Language Processing for Health and Social Media
Abbasi, A. et al., 2014. Social Media Analytics for Smart Health. IEEE Intelligent Systems, 29(2), pp.60—80.</p> </p> Summary In this arti...
Social Media Analytics for Smart Health
Abbasi, A., Adjeroh, D., Dredze, M., Paul, M. J., Zahedi, F. M., Zhao, H., Ross, A. (2014). Social Media Analytics for Smart Health. IEEE Intelligent System...
nlp resources
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G. et al., 2005. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043), p.814. </p> Introd...
noise
A Survey of Types of Text Noise and Techniques to Handle Noisy Text
by Subramaniam, L. V., Roy, S., Faruquie, T. A., & Negi, S. (2009). A survey of types of text noise and techniques to handle noisy text. Proceedings of T...
notions of correctness
Notions of Correctness when Evaluating Protein Name Taggers
by Olsson et al. This paper introduces six notions of correctness to evaluate the performance of protein name taggers: sloppy - which means that the propose...
ontology
Remarks on Ontology Learning and Evaluation
This post contains some random remarks on ontology learning and evaluation: terms versus concepts: concepts are formed by grouping terms with the same meani...
ontology alignment
Basic Ontology Data Integration Concepts
Data integration consists of two basic steps: semantic enrichement mapping discovery LAV vs. GAV</p> LAV and GAV describe two approaches for integrat...
ontology evolution
Using Ontological Contexts to Assess the Relevance of Statements in Ontology Evolution
by Fouad Zablith, Mathieu d'Aquin, Marta Sabou, and Enrico Motta This work describes a method for judging the relevance statements suggested by ontology evol...
ontology integration
Basic Ontology Data Integration Concepts
Data integration consists of two basic steps: semantic enrichement mapping discovery LAV vs. GAV</p> LAV and GAV describe two approaches for integrat...
open information extraction
Automatic knowledge extraction from documents
Fan, J., Kalyanpur, A., Gondek, D. C., & Ferrucci, D. A. (2012). Automatic knowledge extraction from documents. IBM Journal of Research and Development, ...
Ensemble Semantics for Large-scale Unsupervised Relation Extraction
Min, B. et al., 2012. Ensemble semantics for large-scale unsupervised relation extraction. In Proceedings of the 2012 Joint Conference on Empirical Methods ...
Open Information Extraction using Wikipedia
Wu, F. & Weld, D.S., 2010. Open information extraction using Wikipedia. In Proceedings of the 48th Annual Meeting of the Association for Computational Li...
Extraktion von Ternären Relationen aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und...
Open Relation Extraction
[Banko:2008] Banko, Michele and Etzioni, Oren (2008). ''The Tradeoffs Between Open and Traditional Relation Extraction'', Proceedings of ACL-08: HLT, Associa...
opinion holder
Opinion Holder and Target Extraction for Verb-based Opinion Predicates - The Problem is Not Solved
Michael Wiegand, Marc Schulder, & Josef Ruppenhofer. (n.d.). Opinion Holder and Target Extraction for Verb-based Opinion Predicates -- The Problem is No...
opinion mining
Distributional Footprints of Deceptive Product Reviews
by Song Feng, Longfei Xing, Anupam Gogar and Yejin Choi 2012 The authors of this paper argue that there are natural distributions of opinions in reviews for ...
opinion target
Opinion Holder and Target Extraction for Verb-based Opinion Predicates - The Problem is Not Solved
Michael Wiegand, Marc Schulder, & Josef Ruppenhofer. (n.d.). Opinion Holder and Target Extraction for Verb-based Opinion Predicates -- The Problem is No...
optimization
NoDB: Efficient Query Execution on Raw Data Files
Alagiannis, Ioannis, Renata Borovica, Miguel Branco, Stratos Idreos, and Anastasia Ailamaki. NoDB: Efficient Query Execution on Raw Data Files. In Proceedi...
Extracting influential nodes on a social network for information diffusion
by Kimura, M. et al. (Data Mining and Knowledge Discovery 2010; kimura2010) This paper cover the optimization problem of finding the most influential nodes o...
optimized content placement
Targeting Online Communities to Maximise Information Diffusion
Belák, V., Lam, S. & Hayes, C., 2012. Targeting online communities to maximise information diffusion. In Proceedings of the 21st internati...
overview
Beyond Data and Analysis
Davis, C. K. (2014). Beyond Data and Analysis. Commun. ACM, 57(6), 39—41. doi:10.1145/2602326</p> Summary The article identifies competition whi...
Techniques and applications for sentiment analysis
Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82—89. doi:10.1145/2436256.2436274 The articl...
ACM Tech Pack on Business Intelligence and Data Management
Cupoli, P. et al., 2012. ACM Tech Pack on Business Intelligence/Data Management. ACM. Available at: http://techpack.acm.org/bi/. This tech pack contains a hi...
Business Intelligence and Analytics: From Big Data to Big Impact
</p> Chen, H., Chiang, R.H.L. & Storey, V.C., 2012. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), pp.11...
panel
KDIR Panel Discussion
The Information Butler (Andreas Dengel) Learn from best practices Recommends resources (similar to MISTRAL) Context Identification of context ¨(Eye-tra...
parsing
NoDB: Efficient Query Execution on Raw Data Files
Alagiannis, Ioannis, Renata Borovica, Miguel Branco, Stratos Idreos, and Anastasia Ailamaki. NoDB: Efficient Query Execution on Raw Data Files. In Proceedi...
performance
NoDB: Efficient Query Execution on Raw Data Files
Alagiannis, Ioannis, Renata Borovica, Miguel Branco, Stratos Idreos, and Anastasia Ailamaki. NoDB: Efficient Query Execution on Raw Data Files. In Proceedi...
phrase detection
Building and applying a concept hierarchy representation of a user profile
by Nanas et al. The focus on this paper is rather on the building of concept hierarchies and networks describing document repositories than on ontology evalu...
phrase recognition
Evaluating the Impact of Phrase Recognition on Concept Tagging
Mendes, P., Daiber, J., Rajapakse, R., Sasaki, F., & Bizer, C. (2012). Evaluating the Impact of Phrase Recognition on Concept Tagging. In Proceedings of...
polarity shift
Polarity Shift Detection, Elimination and Ensemble: A Three-Stage Model for Document-Level Sentiment Analysis
Xia, Rui, Feng Xu, Jianfei Yu, Yong Qi, and Erik Cambria. Polarity Shift Detection, Elimination and Ensemble: A Three-Stage Model for Document-Level Sentime...
policy informatics
Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security
Chung, W., & Zeng, D. (2016). Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security. Journ...
pooling multinomial classifier
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melvile et al (IBM Watson Research Centre) ***** Analyzing blog posts raises a number of interesting questions: how to identify the subset of blogs discu...
postgres
NoDB: Efficient Query Execution on Raw Data Files
Alagiannis, Ioannis, Renata Borovica, Miguel Branco, Stratos Idreos, and Anastasia Ailamaki. NoDB: Efficient Query Execution on Raw Data Files. In Proceedi...
pre-processing
Verarbeitung von natürlichsprachigen Texten aus Sozialen Netzen
Der Anteil von benutzergenerierten Inhalten hat sich mit der Weiterentwicklung des World Wide Webs zum Web 2.0 beziehungsweise Social Web stark erhöht. Zusät...
precision
On How to Perform a Gold Standard Based Evaluation of Ontology Learning
by K. Dellschaft and St. Staab This work provides an excellent overview of ontology evaluation measures, specifies criteria for good measures and introduces ...
predict sales
Predicting the Future with Social Media
by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...
predictive analytics
Model-Based Forecasting of Significant Societal Events
Ramakrishnan, Naren, Chang-Tien Lu, Madhav V. Marathe, Achla Marathe, Anil Vullikanti, Stephen Eubank, Scotland Leman, et al. Model-Based Forecasting of Sig...
principles
Distributed Information Processing in Biological and Computational systems
Navlakha, S. & Bar-Joseph, Z., 2014. Distributed information processing in biological and computational systems. Communications of the ACM, 58(1), pp.94...
probabilities
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melville et al. (KDD 2009) Motivation: </p> before the rise of the Web 2.0 companies published product information and reviews on Web sites ...
probabily
It Probably Works
Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...
process
The Power of Social Media Analytics
Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 74—81. doi:10.1145/2602574</p> Summa...
product features
A rule-based method for identifying the factor structure in customer satisfaction
Ahmad, A., Dey, L. & Halawani, S.M., 2012. A rule-based method for identifying the factor structure in customer satisfaction. Inf. Sci., 198, pp.118&mda...
project
Employment relations: a data driven analysis of job markets using online job boards and online professional networks
Career websites contain valuable data on employees, their skill sets and, employment history. This article uses k-means clustering on keywords describing ski...
properties
Meme ranking to maximize post virality in microblogging platforms
Bonchi, F., Castillo, C., & Ienco, D. (2013). Meme ranking to maximize posts virality in microblogging platforms. Journal of Intelligent Information Syst...
psml
Envisioning Intelligent Information Technologies through the Prism of Web Intelligence
Zhong et al. (Communications of the ACM) - coined the term Web Intelligence (see literature) This article introduces intelligent Information Technology (iIT)...
recall
On How to Perform a Gold Standard Based Evaluation of Ontology Learning
by K. Dellschaft and St. Staab This work provides an excellent overview of ontology evaluation measures, specifies criteria for good measures and introduces ...
redundancy
Redundancy-based information extraction
The notion of redundancy-based information extraction utilizes the fact that many information on the Web is redundand, which leads to the consequences that ...
regression model
Predicting the Future with Social Media
by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...
regular expressions
Automatic Creation of a Reference Corpus for Political Opinion Mining in User-Generated Content
by Sarmento et al. (TSA 2009) This article presents an approach which applies manually-crafted lexico-syntactic patterns to collect highly opinionated commen...
related concepts
Finding Text Reuse in the Web
by Michael Bendersky and W. Bruce Croft (WSDM'09) This article discusses an approach for finding three different kinds of text reuse in the web: verbatim co...
related sentences
Finding Text Reuse in the Web
by Michael Bendersky and W. Bruce Croft (WSDM'09) This article discusses an approach for finding three different kinds of text reuse in the web: verbatim co...
relation detection
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
relation extraction
Ensemble Semantics for Large-scale Unsupervised Relation Extraction
Min, B. et al., 2012. Ensemble semantics for large-scale unsupervised relation extraction. In Proceedings of the 2012 Joint Conference on Empirical Methods ...
Relation Extraction and the Influence of Automatic Named-Entity Recognition
Giuliano, C., Lavelli, A. & Romano, L., 2007. Relation extraction and the influence of automatic named-entity recognition. ACM Transactions on Speech an...
Collective Cross-Document Relation Extraction Without Labelled Data
Yao, L., Riedel, S. & McCallum, A., 2010. Collective cross-document relation extraction without labelled data. In Proceedings of the 2010 Conference on ...
Open Information Extraction using Wikipedia
Wu, F. & Weld, D.S., 2010. Open information extraction using Wikipedia. In Proceedings of the 48th Annual Meeting of the Association for Computational Li...
Extraktion von Ternären Relationen aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und...
Open Relation Extraction
[Banko:2008] Banko, Michele and Etzioni, Oren (2008). ''The Tradeoffs Between Open and Traditional Relation Extraction'', Proceedings of ACL-08: HLT, Associa...
response rate
Factors Influencing the Response Rate in Social Question and Answering Behavior
Liu, Z. & Jansen, B.J., 2013. Factors Influencing the Response Rate in Social Question and Answering Behavior. In Proceedings of the 2013 Conference on ...
revenue
Discovering company revenue relations from news: A network approach
Ma, Z., Sheng, O.R.L. & Pant, G., 2009. Discovering company revenue relations from news: A network approach. Decission Support Systems, 47(4), pp.408&mda...
reviews
Distributional Footprints of Deceptive Product Reviews
by Song Feng, Longfei Xing, Anupam Gogar and Yejin Choi 2012 The authors of this paper argue that there are natural distributions of opinions in reviews for ...
sarcasm
Techniques and applications for sentiment analysis
Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82—89. doi:10.1145/2436256.2436274 The articl...
scalabiity
Borg, Omega and Kubernetes
Burns, B., Grant, B., Oppenheimer, D., Brewer, E., & Wilkes, J. (2016). Borg, Omega, and Kubernetes. Commun. ACM, 59(5), 50—57. https://doi.org/10...
scalability
Large-scale Incremental Processing Using Distributed Transactions and Notifications
by Peng and Dabek This paper introduces Percolator and the corresponding processing pipeline called Caffeine, which are systems for incrementally processing ...
Dremel: Interactive Analysis of Web-Scale Datasets
by Melnik et al. in Proceedings of the 36th International Conference on Very Large Data Bases 2010 This paper covers Dremel, a scalable, interactive ad-hoc q...
scale
Evaluation and User Preference Study on Spatial Diversity
by Tang and Sanderson (ECIR 2010) This article presents a user study which shows that users prefer search results which are not only (i) relevant but also (i...
self training
Collective Cross-Document Relation Extraction Without Labelled Data
Yao, L., Riedel, S. & McCallum, A., 2010. Collective cross-document relation extraction without labelled data. In Proceedings of the 2010 Conference on ...
semantic knowledge
Ensemble Semantics for Large-scale Unsupervised Relation Extraction
Min, B. et al., 2012. Ensemble semantics for large-scale unsupervised relation extraction. In Proceedings of the 2012 Joint Conference on Empirical Methods ...
semi-supervised learning
Automatische Ermittlung der Relevanz von Nachrichten
Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbest#nde und reichern...
sentic computing
Taking Refuge in Your Personal Sentic Corner
Cambria, E., Hussain, A. & Eckl, C., 2011. Taking Refuge in Your Personal Sentic Corner. In Proceedings of the Workshop on Sentiment Analysis where AI me...
senticnet categories
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
sentiment
Experimental evidence of massive-scale emotional contagion through social networks
Kramer, A. D. I., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of massive-scale emotional contagion through social networks. Proceedi...
sentiment analysis
Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security
Chung, W., & Zeng, D. (2016). Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security. Journ...
Topic-based content and sentiment analysis of Ebola virus on Twitter and in the news
Kim, E. H.-J., Jeong, Y. K., Kim, Y., Kang, K. Y., & Song, M. (2015). Topic-based content and sentiment analysis of Ebola virus on Twitter and in the new...
Opinion Holder and Target Extraction for Verb-based Opinion Predicates - The Problem is Not Solved
Michael Wiegand, Marc Schulder, & Josef Ruppenhofer. (n.d.). Opinion Holder and Target Extraction for Verb-based Opinion Predicates -- The Problem is No...
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
Techniques and applications for sentiment analysis
Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82—89. doi:10.1145/2436256.2436274 The articl...
Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions
Lau, R. et al., 2012. Web 2.0 Environmental Scanning and Adaptive Decision Support for Business Mergers and Acquisitions. Management Information Systems Qua...
Taking Refuge in Your Personal Sentic Corner
Cambria, E., Hussain, A. & Eckl, C., 2011. Taking Refuge in Your Personal Sentic Corner. In Proceedings of the Workshop on Sentiment Analysis where AI me...
Sentimantics: Lexical Sentiment Polarity Representations with Contextuality
Das, A. & Gambäck, B., 2012. Sentimantics: conceptual spaces for lexical sentiment polarity representation with contextuality. In Proceedi...
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melville et al. (KDD 2009) Motivation: </p> before the rise of the Web 2.0 companies published product information and reviews on Web sites ...
Isanette: A Common and Common Sense Knowledge Base for Opinion Mining
Cambria, E. et al., 2011. Isanette: A Common and Common Sense Knowledge Base for Opinion Mining. In Data Mining Workshops (ICDMW), 2011 IEEE 11th Internation...
sentiment calculation rules
Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards
Thet, Tun Thura, Jin-Cheon Na, and Christopher S. G. Khoo. Aspect-Based Sentiment Analysis of Movie Reviews on Discussion Boards. Journal of Information Scie...
sentiment detection
Generating High-Coverage Semantic Orientation Lexicons from Overtly Marked Words and a Thesaurus
by Saif et al. 1. General confirms the Polyanna Hypothesis which states that people have a preference for using positive words and expressions suggesting th...
sentiment lexicon
Generating High-Coverage Semantic Orientation Lexicons from Overtly Marked Words and a Thesaurus
by Saif et al. 1. General confirms the Polyanna Hypothesis which states that people have a preference for using positive words and expressions suggesting th...
The viability of web-derived polarity lexicons
by Velikovich et al. (Google research) This paper describes an approach for semi-automatically generating sentiment lexicon from seed terms and a Web corpus...
sentiment terms
Generating High-Coverage Semantic Orientation Lexicons from Overtly Marked Words and a Thesaurus
by Saif et al. 1. General confirms the Polyanna Hypothesis which states that people have a preference for using positive words and expressions suggesting th...
sentiment topics
Leveraging Sentiment Analysis for Topic Detection
by Cai et al (IBM China Research Lab) *** The authors combine sentiment detection with identifying the terms that are highly correlated to a specific sentime...
sentiwordnet
Sentimantics: Lexical Sentiment Polarity Representations with Contextuality
Das, A. & Gambäck, B., 2012. Sentimantics: conceptual spaces for lexical sentiment polarity representation with contextuality. In Proceedi...
shortcomings
Opinion Holder and Target Extraction for Verb-based Opinion Predicates - The Problem is Not Solved
Michael Wiegand, Marc Schulder, & Josef Ruppenhofer. (n.d.). Opinion Holder and Target Extraction for Verb-based Opinion Predicates -- The Problem is No...
similarity metrics
Ensemble Semantics for Large-scale Unsupervised Relation Extraction
Min, B. et al., 2012. Ensemble semantics for large-scale unsupervised relation extraction. In Proceedings of the 2012 Joint Conference on Empirical Methods ...
singular value decomposition
Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis
Cambria, E., Song, Y., Wang, H., & Howard, N. (2013). Semantic Multi-Dimensional Scaling for Open-Domain Sentiment Analysis. IEEE Intelligent Systems, 9...
Digital Intuition: Applying Common Sense Using Dimensionality Reduction
Havasi, C., Pustejovsky, J., Speer, R., & Lieberman, H. (2009). Digital Intuition: Applying Common Sense Using Dimensionality Reduction. Intelligent Syst...
smart cities
The New Smart Cities
Mone, G. (2015). The New Smart Cities. Commun. ACM, 58(7), 20—21. http://doi.org/10.1145/2771297</p> </p> Summary This article discusses b...
social media
The Power of Social Media Analytics
Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 74—81. doi:10.1145/2602574</p> Summa...
Social Media Analytics for Smart Health
Abbasi, A., Adjeroh, D., Dredze, M., Paul, M. J., Zahedi, F. M., Zhao, H., Ross, A. (2014). Social Media Analytics for Smart Health. IEEE Intelligent System...
Meme ranking to maximize post virality in microblogging platforms
Bonchi, F., Castillo, C., & Ienco, D. (2013). Meme ranking to maximize posts virality in microblogging platforms. Journal of Intelligent Information Syst...
social metrics
Catching a Viral Video
Broxton, Tom, Yannet Interian, Jon Vaver, and Mirjam Wattenhofer. Catching a Viral Video. Journal of Intelligent Information Systems 40, no. 2 (April 1, 201...
social network
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G. et al., 2005. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 435(7043), p.814. </p> Introd...
Thematic Exploration of Linked Data
by Castano et al.; Very Large Data Search (VLDS) 2011 This article addresses the problem of organizing linked data, which features an inherent flat organizat...
Extracting influential nodes on a social network for information diffusion
by Kimura, M. et al. (Data Mining and Knowledge Discovery 2010; kimura2010) This paper cover the optimization problem of finding the most influential nodes o...
social network analysis
Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security
Chung, W., & Zeng, D. (2016). Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security. Journ...
social question answering
Factors Influencing the Response Rate in Social Question and Answering Behavior
Liu, Z. & Jansen, B.J., 2013. Factors Influencing the Response Rate in Social Question and Answering Behavior. In Proceedings of the 2013 Conference on ...
social sciences
Evaluation Without Ground Truth in Social Media Research
Zafarani, Reza, and Huan Liu. Evaluation Without Ground Truth in Social Media Research. Communcations of the ACM 58, no. 6 (May 2015): 54—60. doi:10.1...
soical networks
Social influence analysis in large-scale networks
by Tang et al. (tang2009), SIGKDD Tang et al. (2009) propose Topical Affinity Propagation (TAP) for determining the topic-level social influence of nodes in ...
spatial
Spatial and Temporal Information
based on "Normalizing Spatial Information to Better Combine Criteria in Geographical Information Retrieval" y Palacio et al. (ECIR 2009). There are two types...
spectral association
Taking Refuge in Your Personal Sentic Corner
Cambria, E., Hussain, A. & Eckl, C., 2011. Taking Refuge in Your Personal Sentic Corner. In Proceedings of the Workshop on Sentiment Analysis where AI me...
speculation detection
A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis
Cruz, Noa P., Maite Taboada, and Ruslan Mitkov. A Machine-Learning Approach to Negation and Speculation Detection for Sentiment Analysis. Journal of the As...
spreading activation
Taking Refuge in Your Personal Sentic Corner
Cambria, E., Hussain, A. & Eckl, C., 2011. Taking Refuge in Your Personal Sentic Corner. In Proceedings of the Workshop on Sentiment Analysis where AI me...
statistics
It Probably Works
Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...
Sentiment Analysis of Blogs by Combining Lexical Knowledge with Text Classification
by Melville et al. (KDD 2009) Motivation: </p> before the rise of the Web 2.0 companies published product information and reviews on Web sites ...
stochastic gradient descent
Clash of the Contagions - Cooperation and Competition in Information Diffusion
by Seth A. Myers and Jure Leskovec, IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium Introduction The authors present a statistica...
structural semantic interconnection
Domain relevance of terminology
based on Navigli, R. and Velardi, P. (2004). ''Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites'', Computational Linguistics, page...
support vector machines
Relation Extraction and the Influence of Automatic Named-Entity Recognition
Giuliano, C., Lavelli, A. & Romano, L., 2007. Relation extraction and the influence of automatic named-entity recognition. ACM Transactions on Speech an...
taxonomic overlap
On How to Perform a Gold Standard Based Evaluation of Ontology Learning
by K. Dellschaft and St. Staab This work provides an excellent overview of ontology evaluation measures, specifies criteria for good measures and introduces ...
technologies
Data Warehousing and Analytics Infrastructure at Facebook
Thusoo, A. et al., 2010. Data warehousing and analytics infrastructure at facebook. In Proceedings of the 2010 ACM SIGMOD International Conference on Managem...
temporal
Spatial and Temporal Information
based on "Normalizing Spatial Information to Better Combine Criteria in Geographical Information Retrieval" y Palacio et al. (ECIR 2009). There are two types...
term weighting
Taking Refuge in Your Personal Sentic Corner
Cambria, E., Hussain, A. & Eckl, C., 2011. Taking Refuge in Your Personal Sentic Corner. In Proceedings of the Workshop on Sentiment Analysis where AI me...
terminology
Remarks on Ontology Learning and Evaluation
This post contains some random remarks on ontology learning and evaluation: terms versus concepts: concepts are formed by grouping terms with the same meani...
Detecting Geographic Locations from Web Resources
by Wang et al. (GIR 2005) The articles of the author distinguish between three different types of geographic locations the provider location (= source locat...
text classification
Natural Language Processing for Health and Social Media
Abbasi, A. et al., 2014. Social Media Analytics for Smart Health. IEEE Intelligent Systems, 29(2), pp.60—80.</p> </p> Summary In this arti...
Web Page Classification: Features and Algorithms
Qi, X. & Davison, B.D., 2009. Web page classification: Features and algorithms. ACM Comput. Surv., 41(2), pp.12:1—12:31. </p> </p> C...
A Survey of Types of Text Noise and Techniques to Handle Noisy Text
by Subramaniam, L. V., Roy, S., Faruquie, T. A., & Negi, S. (2009). A survey of types of text noise and techniques to handle noisy text. Proceedings of T...
text cleanup
Verarbeitung von natürlichsprachigen Texten aus Sozialen Netzen
Der Anteil von benutzergenerierten Inhalten hat sich mit der Weiterentwicklung des World Wide Webs zum Web 2.0 beziehungsweise Social Web stark erhöht. Zusät...
text mining
Distributional Footprints of Deceptive Product Reviews
by Song Feng, Longfei Xing, Anupam Gogar and Yejin Choi 2012 The authors of this paper argue that there are natural distributions of opinions in reviews for ...
Extraktion von Ternären Relationen aus deutschsprachigen Texten
Einleitung Aktuelle Web Intelligence Systeme wie der Media Watch on Climate Change (www.ecoresearch.net/climate) analysieren umfangreiche Datenbestände und...
text reuse
Finding Text Reuse in the Web
by Michael Bendersky and W. Bruce Croft (WSDM'09) This article discusses an approach for finding three different kinds of text reuse in the web: verbatim co...
text search
Suffix array
The suffix array is a memory-efficient alternative to the suffix tree which provides a sorted list of string indices indicating the string’s suffixes.
40 years of suffix trees
Suffix trees are used in text searching, indexing, statistics. This article describes the history, construction, current developments and applications of suf...
topic detection
Using Word Association to Detect Multitopic Structures in Text Documents
Klahold, A. et al., 2014. Using Word Association to Detect Multitopic Structures in Text Documents. IEEE Intelligent Systems, 29(5), pp.40—46.</p&g...
topic model
Topic-based content and sentiment analysis of Ebola virus on Twitter and in the news
Kim, E. H.-J., Jeong, Y. K., Kim, Y., Kang, K. Y., & Song, M. (2015). Topic-based content and sentiment analysis of Ebola virus on Twitter and in the new...
topic sentiment
Topic-based content and sentiment analysis of Ebola virus on Twitter and in the news
Kim, E. H.-J., Jeong, Y. K., Kim, Y., Kang, K. Y., & Song, M. (2015). Topic-based content and sentiment analysis of Ebola virus on Twitter and in the new...
Natural Language Processing for Health and Social Media
Abbasi, A. et al., 2014. Social Media Analytics for Smart Health. IEEE Intelligent Systems, 29(2), pp.60—80.</p> </p> Summary In this arti...
Predicting the Future with Social Media
by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...
Ermittlung der Valenz von Nachrichten in Sozialen Netzen
Die Valenz (Sentiment; Semantic Orientation) eines Dokumentes definiert, ob dieses eine positive oder negative Polarität beziehungsweise Berichterstattung au...
undersampling
Mining competitor relationships from online news: A network based approach
Ma, Z., Pant, G. & Sheng, O.R.L., 2011. Mining competitor relationships from online news: A network-based approach. Electronic Commerce Research and Appl...
user evaluation
Evaluation and User Preference Study on Spatial Diversity
by Tang and Sanderson (ECIR 2010) This article presents a user study which shows that users prefer search results which are not only (i) relevant but also (i...
Judging the spatial relevance of documents for GIR
by Clough and Joho (Advances in Information Retrieval 2006) This articles describes a pilot study which assesses both thematic and geographic relevance based...
user generated content
Ermittlung der Valenz von Nachrichten in Sozialen Netzen
Die Valenz (Sentiment; Semantic Orientation) eines Dokumentes definiert, ob dieses eine positive oder negative Polarität beziehungsweise Berichterstattung au...
user participation
Online Discussion Participation Prediction Using Non-Negative Matrix Factorization
Fung, Y.-H., Li, C.-H., & Cheung, W. K. (2007). Online Discussion Participation Prediction Using Non-negative Matrix Factorization. In Proceedings of th...
user preferences
Online Discussion Participation Prediction Using Non-Negative Matrix Factorization
Fung, Y.-H., Li, C.-H., & Cheung, W. K. (2007). Online Discussion Participation Prediction Using Non-negative Matrix Factorization. In Proceedings of th...
viral videos
Catching a Viral Video
Broxton, Tom, Yannet Interian, Jon Vaver, and Mirjam Wattenhofer. Catching a Viral Video. Journal of Intelligent Information Systems 40, no. 2 (April 1, 201...
watson
Automatic knowledge extraction from documents
Fan, J., Kalyanpur, A., Gondek, D. C., & Ferrucci, D. A. (2012). Automatic knowledge extraction from documents. IBM Journal of Research and Development, ...
weak supervision
Collective Cross-Document Relation Extraction Without Labelled Data
Yao, L., Riedel, S. & McCallum, A., 2010. Collective cross-document relation extraction without labelled data. In Proceedings of the 2010 Conference on ...
web intelligence
Model-Based Forecasting of Significant Societal Events
Ramakrishnan, Naren, Chang-Tien Lu, Madhav V. Marathe, Achla Marathe, Anil Vullikanti, Stephen Eubank, Scotland Leman, et al. Model-Based Forecasting of Sig...
The Power of Social Media Analytics
Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 74—81. doi:10.1145/2602574</p> Summa...
Healthcare Intelligence: Turing Data Into Knowledge
Yang, H., Kundakcioglu, E., Li, J., Wu, T., Mitchell, J. R., Hara, A., Tsui, K.-L. (2014). Healthcare Intelligence: Turning Data into Knowledge. IEEE Intell...
Big Data and Its Technical Challenges
Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big Data and Its Technical Chal...
Web Intelligence Applications
This article collects real world use cases of Web and Business Intelligence applications. Use Cases Business Intelligence: companies use their own data sourc...
Business Intelligence and Analytics: From Big Data to Big Impact
</p> Chen, H., Chiang, R.H.L. & Storey, V.C., 2012. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), pp.11...
A rule-based method for identifying the factor structure in customer satisfaction
Ahmad, A., Dey, L. & Halawani, S.M., 2012. A rule-based method for identifying the factor structure in customer satisfaction. Inf. Sci., 198, pp.118&mda...
Envisioning Intelligent Information Technologies through the Prism of Web Intelligence
Zhong et al. (Communications of the ACM) - coined the term Web Intelligence (see literature) This article introduces intelligent Information Technology (iIT)...
Data Mining for Web Intelligence
by Han and Chen-Chuan This article discusses data mining as key technology for bringing intelligence and direction to our Web interactions. At first they dis...
web portals
Envisioning Intelligent Information Technologies through the Prism of Web Intelligence
Zhong et al. (Communications of the ACM) - coined the term Web Intelligence (see literature) This article introduces intelligent Information Technology (iIT)...
web search
Data Mining for Web Intelligence
by Han and Chen-Chuan This article discusses data mining as key technology for bringing intelligence and direction to our Web interactions. At first they dis...
wikipedia
From Names to Entities using Thematic Context Distance
Pilz, A., & Paaß, G. (2011). From Names to Entities Using Thematic Context Distance. In Proceedings of the 20th ACM International Conference...
Evaluating Entity Linking with Wikipedia
Hachey, B. et al., 2013. Evaluating Entity Linking with Wikipedia. Artificial Intelligence, 194, pp.130—150. This article compares the performance of t...
Open Information Extraction using Wikipedia
Wu, F. & Weld, D.S., 2010. Open information extraction using Wikipedia. In Proceedings of the 48th Annual Meeting of the Association for Computational Li...
wisdom web
Envisioning Intelligent Information Technologies through the Prism of Web Intelligence
Zhong et al. (Communications of the ACM) - coined the term Web Intelligence (see literature) This article introduces intelligent Information Technology (iIT)...
word relevance
Polarity Shift Detection, Elimination and Ensemble: A Three-Stage Model for Document-Level Sentiment Analysis
Xia, Rui, Feng Xu, Jianfei Yu, Yong Qi, and Erik Cambria. Polarity Shift Detection, Elimination and Ensemble: A Three-Stage Model for Document-Level Sentime...
word sense disambiguation
Word Sense Disambiguation for Automatic Taxonomy Construction from Text-Based Web Corpora
by de Knijff et al. This paper covers a framework that extracts terms from Web corpora, uses word sense disambiguation (WSD) to determine the word's senses,...
A conceptual density-based approach for disambiguation of toponyms
by Buscaldi and RossoThis article explores the use of word-sense-disambiguation (WSD) techniques for toponym resolution. The authors explain two algorithms w...
word support
Leveraging Sentiment Analysis for Topic Detection
by Cai et al (IBM China Research Lab) *** The authors combine sentiment detection with identifying the terms that are highly correlated to a specific sentime...