Abstract
The statistical measures for similarity have been widely used in textual information retrieval for many decades. They are the basis to improve the effectiveness ofIR 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 oft his 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.
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Takano, A. et al. (2000). Information Access Based on Associative Calculation. In: Hlaváč, V., Jeffery, K.G., Wiedermann, J. (eds) SOFSEM 2000: Theory and Practice of Informatics. SOFSEM 2000. Lecture Notes in Computer Science, vol 1963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44411-4_12
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DOI: https://doi.org/10.1007/3-540-44411-4_12
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