Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Models for retrieval with probabilistic indexing
Information Processing and Management: an International Journal - Modeling data, information and knowledge
Word association norms, mutual information, and lexicography
Computational Linguistics
ACM Transactions on Information Systems (TOIS)
Information retrieval using pathfinder networks
Pathfinder associative networks
An evaluation of phrasal and clustered representations on a text categorization task
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the first ACM international conference on Digital libraries
Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
A method of measuring term representativeness: baseline method using co-occurrence distribution
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Hierarchical Bayesian clustering for automatic text classification
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
An early warning support system for food safety risks
JSAI'05 Proceedings of the 2005 international conference on New Frontiers in Artificial Intelligence
Shifting concepts to their associative concepts via bridges
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
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The statistical measures for similarity have been widely used in textual information retrieval for many decades. They are the basis to improve the effectiveness of IR systems, including retrieval, clustering, and summarization. We have developed an information retrieval system DualNAVI which provides users with rich interaction both in document space and in word space. We show that associative calculation for measuring similarity among documents or words is the computational basis of this effective information access with DualNAVI. The new approaches in document clustering (Hierarchical Bayesian Clustering), and measuring term representativeness (Baseline method) are also discussed. Both have sound mathematical basis and depend essentially on associative calculation.