Affiliation:
1. Miami Univ., Oxford, OH
Abstract
Clustering of very large document databases is useful for both searching and browsing. The periodic updating of clusters is required due to the dynamic nature of databases. An algorithm for incremental clustering is introduced. The complexity and cost analysis of the algorithm together with an investigation of its expected behavior are presented. Through empirical testing it is shown that the algorithm achieves cost effectiveness and generates statistically valid clusters that are compatible with those of reclustering. The experimental evidence shows that the algorithm creates an effective and efficient retrieval environment.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications,General Business, Management and Accounting,Information Systems
Cited by
75 articles.
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