Tags

Amazon Mechanical Turk

BDM

BI metrics

Big data

Rich Data, Poor Fields

less than 1 minute read

This article shows how handheld devices and big data technology may multiply field yields and make farming more environmentally friendly.

Data Science and Prediction

3 minute read

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...

CIMAWA

ConceptNet

Crowdsourcing

Data Mining

Most Influential Data Mining Algorithms

less than 1 minute read

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

less than 1 minute read

based on "Normalizing Spatial Information to Better Combine Criteria in Geographical Information Retrieval" y Palacio et al. (ECIR 2009). There are two types...

Forum

Freebase

Geo

Spatial and Temporal Information

less than 1 minute read

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

less than 1 minute read

basierend auf Ideen aus dem Beitrag "Perspektiven der Wirtschaftsinformatik aus Sicht der Informatik" von Matthias Jarke Das relationale Datenmodell (Codd 19...

HITS algorithm

Hearst Pattern

Information Retrieval

Ontology Building

Ontology Evaluation

PMI

POS tagger

ProBase

Sentiment Detection

Talks

KDIR causal knowledge

less than 1 minute read

</p> Automatic identification of quasi-experimental designs for discovering causal knowledge by Jensen et. al</p> Introduction </p> blac...

TnT

WISE 2011

Web Intelligence

algorithms

It Probably Works

3 minute read

Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...

application

applications

Rich Data, Poor Fields

less than 1 minute read

This article shows how handheld devices and big data technology may multiply field yields and make farming more environmentally friendly.

The New Smart Cities

less than 1 minute read

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

2 minute read

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...

Big Data and Its Technical Challenges

1 minute read

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

1 minute read

This article collects real world use cases of Web and Business Intelligence applications. Use Cases Business Intelligence: companies use their own data sourc...

architecture

argument-based machine learning

Argument-based Machine Learning

less than 1 minute read

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

aspect-based sentiment analysis

average uninterpolated precision

background knowledge

basics

big data

The Pathologies of Big data

less than 1 minute read

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

bot detection

The DARPA Twitter Bot Challenge

1 minute read

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

1 minute read

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

less than 1 minute read

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

Web Intelligence Applications

1 minute read

This article collects real world use cases of Web and Business Intelligence applications. Use Cases Business Intelligence: companies use their own data sourc...

business metrics

categorization

challenges

Big Data and Its Technical Challenges

1 minute read

Jagadish, H. V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J. M., Ramakrishnan, R., & Shahabi, C. (2014). Big Data and Its Technical Chal...

classification

clique

clique percolation method

Thematic Exploration of Linked Data

1 minute read

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

Thematic Exploration of Linked Data

1 minute read

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

co-reference resolution

common knowledge

common sense knowledge

comparative sentiment analysis

components

concept

Extracting Concepts

less than 1 minute read

This article collects some thoughts on normalizing phrases to concepts. Examples: drive_car <- "drive a car", "you drive your car", "driving cars" and "...

concept tagging

concept-based sentiment analysis

conference

constraints

container infrastructure

Borg, Omega and Kubernetes

less than 1 minute read

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

2 minute read

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

Catching a Viral Video

2 minute read

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

Catching a Viral Video

2 minute read

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

contextualization

corpora

Evaluation in Information Retrieval

2 minute read

Manning, C.D., Raghavan, P. & Schütze, H., 2008. Introduction to Information Retrieval 1st ed., Cambridge University Press. Chapter 8 - Evaluation in inf...

corpus

corpus creation

creation

criteria for evaluation measures

curation

Checking Facts

less than 1 minute read

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?

less than 1 minute read

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

data integration

data loading

data management

data mining

Data Mining for Web Intelligence

less than 1 minute read

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

3 minute read

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

1 minute read

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

less than 1 minute read

Suffix trees are used in text searching, indexing, statistics. This article describes the history, construction, current developments and applications of suf...

Data sketching

less than 1 minute read

This article introduces three popular data structures that efficiently handle and summarize large data sets.

date extraction

Finding Text Reuse in the Web

less than 1 minute read

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

deceptive reviews

deep learning

Growing Pains for Deep Learning

1 minute read

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

deployment

Borg, Omega and Kubernetes

less than 1 minute read

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

less than 1 minute read

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

discussion

KDIR Panel Discussion

less than 1 minute read

The Information Butler (Andreas Dengel) Learn from best practices Recommends resources (similar to MISTRAL) Context Identification of context ¨(Eye-tra...

distant supervision

docker

Borg, Omega and Kubernetes

less than 1 minute read

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

less than 1 minute read

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

less than 1 minute read

based on Navigli, R. and Velardi, P. (2004). ''Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites'', Computational Linguistics, page...

domain specificity

domain specifity

dremel

e-government

Text-Mining the Voice of the People

1 minute read

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

3 minute read

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

emotional contagion

epistemology

Data Science and Prediction

3 minute read

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

evaluation

Evaluating Entity Linking with Wikipedia

1 minute read

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

2 minute read

Manning, C.D., Raghavan, P. & Schütze, H., 2008. Introduction to Information Retrieval 1st ed., Cambridge University Press. Chapter 8 - Evaluation in inf...

Remarks on Ontology Learning and Evaluation

less than 1 minute read

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

evaluation measure

experiment design

facebook

fact checking

Checking Facts

less than 1 minute read

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

less than 1 minute read

This article shows how handheld devices and big data technology may multiply field yields and make farming more environmentally friendly.

feature scaling

feature selection

features

The DARPA Twitter Bot Challenge

1 minute read

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....

flameware detection

framework

future internet

The Pathologies of Big data

less than 1 minute read

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

geo-tagger-evaluation

geo-tagging

geospatial

german

global context

google

grammar rules

graph-based disambiguation

graph-based models

health

Social Media Analytics for Smart Health

less than 1 minute read

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

heuristics

hierarchical classification

high number of parameters

hive

hotspot detection

ikt

imbalanced data sets

impact

implicit network connections

importance

incremental processing

influence

influence bots

The DARPA Twitter Bot Challenge

1 minute read

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

2 minute read

Broxton, Tom, Yannet Interian, Jon Vaver, and Mirjam Wattenhofer. Catching a Viral Video. Journal of Intelligent Information Systems 40, no. 2 (April 1, 201...

information extraction

Redundancy-based information extraction

less than 1 minute read

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

information spaces

Data Mining for Web Intelligence

less than 1 minute read

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

1 minute read

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

less than 1 minute read

</p> Automatic identification of quasi-experimental designs for discovering causal knowledge by Jensen et. al</p> Introduction </p> blac...

kdir2009

KDIR Panel Discussion

less than 1 minute read

The Information Butler (Andreas Dengel) Learn from best practices Recommends resources (similar to MISTRAL) Context Identification of context ¨(Eye-tra...

keyword analysis

keyword extraction

knowledge extraction

language resources

latent dirichlet allocation

latent semantic analysis

lexico-syntactic patterns

lexicon expansion

lexicons

lidstone smoothing

linear discriminant analysis

linked open data

Thematic Exploration of Linked Data

1 minute read

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

local context

locality sensitive hashing

It Probably Works

3 minute read

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

lsa

Text-Mining the Voice of the People

1 minute read

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

3 minute read

Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...

machine learning

Argument-based Machine Learning

less than 1 minute read

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

map reduce

market predictors

Predicting the Future with Social Media

2 minute read

by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...

market research

matrix

method

methods

Most Influential Data Mining Algorithms

less than 1 minute read

As ranked by the IEEE International Conference on Data Mining2006 (ICDM 2006) C4.5 k-means support vector machines (SVM) Apriori expectation maximization (...

metrics

Evaluating Entity Linking with Wikipedia

1 minute read

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

2 minute read

Manning, C.D., Raghavan, P. & Schütze, H., 2008. Introduction to Information Retrieval 1st ed., Cambridge University Press. Chapter 8 - Evaluation in inf...

micro blogging

misq

What makes a helpful online Review?

less than 1 minute read

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

2 minute read

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

mtp

multi-dimensional scaling

multitopic detection

naive bayes

named entity disambiguation

named entity linking

Evaluating Entity Linking with Wikipedia

1 minute read

Hachey, B. et al., 2013. Evaluating Entity Linking with Wikipedia. Artificial Intelligence, 194, pp.130—150. This article compares the performance of t...

named entity recognition

named entity recogniton

named entity resolution

negation

network

network inferrence

networks

neural network

Growing Pains for Deep Learning

1 minute read

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

nlp

Social Media Analytics for Smart Health

less than 1 minute read

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

noise

notions of correctness

ontology

Remarks on Ontology Learning and Evaluation

less than 1 minute read

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

less than 1 minute read

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

ontology integration

Basic Ontology Data Integration Concepts

less than 1 minute read

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

Open Relation Extraction

less than 1 minute read

[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 mining

opinion target

optimization

optimized content placement

overview

Beyond Data and Analysis

1 minute read

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...

panel

KDIR Panel Discussion

less than 1 minute read

The Information Butler (Andreas Dengel) Learn from best practices Recommends resources (similar to MISTRAL) Context Identification of context ¨(Eye-tra...

parsing

performance

phrase detection

phrase recognition

polarity shift

policy informatics

pooling multinomial classifier

postgres

pre-processing

precision

predict sales

Predicting the Future with Social Media

2 minute read

by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...

predictive analytics

principles

probabilities

probabily

It Probably Works

3 minute read

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

2 minute read

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

project

properties

psml

recall

redundancy

Redundancy-based information extraction

less than 1 minute read

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

2 minute read

by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...

regular expressions

Finding Text Reuse in the Web

less than 1 minute read

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...

Finding Text Reuse in the Web

less than 1 minute read

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

relation extraction

Open Relation Extraction

less than 1 minute read

[Banko:2008] Banko, Michele and Etzioni, Oren (2008). ''The Tradeoffs Between Open and Traditional Relation Extraction'', Proceedings of ACL-08: HLT, Associa...

response rate

revenue

reviews

sarcasm

scalabiity

Borg, Omega and Kubernetes

less than 1 minute read

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

scale

self training

semantic knowledge

semi-supervised learning

sentic computing

senticnet categories

sentiment

sentiment analysis

sentiment calculation rules

sentiment detection

sentiment lexicon

sentiment terms

sentiment topics

sentiwordnet

shortcomings

similarity metrics

singular value decomposition

smart cities

The New Smart Cities

less than 1 minute read

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

2 minute read

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

less than 1 minute read

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...

social metrics

Catching a Viral Video

2 minute read

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

Thematic Exploration of Linked Data

1 minute read

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...

social network analysis

social question answering

social sciences

soical networks

spatial

Spatial and Temporal Information

less than 1 minute read

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

speculation detection

spreading activation

statistics

It Probably Works

3 minute read

Mcmullen, T. (2015). It Probably Works. Commun. ACM, 58(11), 50—54. http://doi.org/10.1145/2814332 Introduction This article distinguishes between thre...

stochastic gradient descent

structural semantic interconnection

Domain relevance of terminology

less than 1 minute read

based on Navigli, R. and Velardi, P. (2004). ''Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites'', Computational Linguistics, page...

support vector machines

taxonomic overlap

technologies

temporal

Spatial and Temporal Information

less than 1 minute read

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

terminology

Remarks on Ontology Learning and Evaluation

less than 1 minute read

This post contains some random remarks on ontology learning and evaluation: terms versus concepts: concepts are formed by grouping terms with the same meani...

text classification

text cleanup

text mining

text reuse

Finding Text Reuse in the Web

less than 1 minute read

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...

Suffix array

1 minute read

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

less than 1 minute read

Suffix trees are used in text searching, indexing, statistics. This article describes the history, construction, current developments and applications of suf...

topic detection

topic model

topic sentiment

twitter

Predicting the Future with Social Media

2 minute read

by Asur, S., & Huberman, B. A. (2010). IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)</p> <...

undersampling

user evaluation

user generated content

user participation

user preferences

viral videos

Catching a Viral Video

2 minute read

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

weak supervision

web intelligence

The Power of Social Media Analytics

2 minute read

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...

Big Data and Its Technical Challenges

1 minute read

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

1 minute read

This article collects real world use cases of Web and Business Intelligence applications. Use Cases Business Intelligence: companies use their own data sourc...

Data Mining for Web Intelligence

less than 1 minute read

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

Data Mining for Web Intelligence

less than 1 minute read

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

Evaluating Entity Linking with Wikipedia

1 minute read

Hachey, B. et al., 2013. Evaluating Entity Linking with Wikipedia. Artificial Intelligence, 194, pp.130—150. This article compares the performance of t...

wisdom web

word relevance

word sense disambiguation

word support