| K. Eguchi. Adaptive Cluster-based Browsing Using Incrementally Expanded Queries and Its Effects. In ACM SIGIR 99, pages 265--266, 1999. |
....which match almost perfectly the existing topics of the corpus. 1. MOTIVATION Unsupervised document clustering is a central problem in information retrieval. Possible applications includes use of clustering for improving retrieval [19] and for navigating and browsing large document collections [3, 6, 20]. Several recent works suggest to use clustering techniques for unsupervised document classi cation [15, 5, 17] In this task, we are given a collection of unlabeled documents and requested to nd clusters that are highly correlated with the true topics of the documents. This practical situation ....
K. Eguchi. Adaptive Cluster-based Browsing Using Incrementally Expanded Queries and Its Eects. In ACM SIGIR 99, pages 265-266, 1999.
.... effectiveness of document retrieval systems by first grouping the documents into clusters (cf. 27] and the references therein) Recently, document clustering has been put forward as an important tool for Web search engines [15] 16] 18] 30] navigating and browsing document collections [5] 6] [8] [9] 23] and distributed retrieval [29] Two types of clustering have been studied in the context of information retrieval systems: clustering the documents on the basis of the distributions of words that co occur in the documents, and clustering the words using the distributions of the documents ....
K. Eguchi. Adaptive Cluster-based Browsing Using Incrementally Expanded Queries and Its Effects. In ACM SIGIR 99, pages 265--266, 1999.
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K. Eguchi. Adaptive Cluster-based Browsing Using Incrementally Expanded Queries and Its Effects. In ACM SIGIR 99, pages 265--266, 1999.
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