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ACM Transactions on Information Systems (TOIS), Volume 26 Issue 3, June 2008

Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
Ahmed Abbasi, Hsinchun Chen, Arab Salem
Article No.: 12
DOI: 10.1145/1361684.1361685

The Internet is frequently used as a medium for exchange of information and opinions, as well as propaganda dissemination. In this study the use of sentiment analysis methodologies is proposed for classification of Web forum opinions in multiple...

Interpreting TF-IDF term weights as making relevance decisions
Ho Chung Wu, Robert Wing Pong Luk, Kam Fai Wong, Kui Lam Kwok
Article No.: 13
DOI: 10.1145/1361684.1361686

A novel probabilistic retrieval model is presented. It forms a basis to interpret the TF-IDF term weights as making relevance decisions. It simulates the local relevance decision-making for every location of a document, and combines all of these...

A basis for information retrieval in context
Massimo Melucci
Article No.: 14
DOI: 10.1145/1361684.1361687

Information retrieval (IR) models based on vector spaces have been investigated for a long time. Nevertheless, they have recently attracted much research interest. In parallel, context has been rediscovered as a crucial issue in information...

Incremental cluster-based retrieval using compressed cluster-skipping inverted files
Ismail Sengor Altingovde, Engin Demir, Fazli Can, Özgür Ulusoy
Article No.: 15
DOI: 10.1145/1361684.1361688

We propose a unique cluster-based retrieval (CBR) strategy using a new cluster-skipping inverted file for improving query processing efficiency. The new inverted file incorporates cluster membership and centroid information along with the usual...

Unified relevance models for rating prediction in collaborative filtering
Jun Wang, Arjen P. de Vries, Marcel J. T. Reinders
Article No.: 16
DOI: 10.1145/1361684.1361689

Collaborative filtering aims at predicting a user's interest for a given item based on a collection of user profiles. This article views collaborative filtering as a problem highly related to information retrieval, drawing an analogy between the...

Assessing multivariate Bernoulli models for information retrieval
David E. Losada, Leif Azzopardi
Article No.: 17
DOI: 10.1145/1361684.1361690

Although the seminal proposal to introduce language modeling in information retrieval was based on a multivariate Bernoulli model, the predominant modeling approach is now centered on multinomial models. Language modeling for retrieval based on...