Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
Unsupervised document classification using sequential information maximization
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
P-TAG: large scale automatic generation of personalized annotation tags for the web
Proceedings of the 16th international conference on World Wide Web
On the conceptual tag refinement
Proceedings of the 2008 ACM symposium on Applied computing
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The contribution of this paper includes three folders: (1) To introduce a topic-oriented query expansion model based on the Information Bottleneck theory that classify terms into distinct topical clusters in order to find out candidate terms for the query expansion. (2) To define a term-term similarity matrix that is available to improve the term ambiguous problem. (3) To propose two measures, intracluster and intercluster similarities, that are based on proximity between the topics represented by two clusters in order to evaluate the retrieval effectiveness. Results of several evaluation experiments in Web search exhibit the average intracluster similarity was improved for the gain of 79.1% while the average intercluster similarity was decreased for the loss of 36.0%.