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  • 标题:Incremental Transitivity Applied to Cluster Retrieval
  • 本地全文:下载
  • 作者:Yaser Hasan ; Muhammad Hassan ; Mick Ridley
  • 期刊名称:The International Arab Journal of Information Technology
  • 印刷版ISSN:1683-3198
  • 出版年度:2008
  • 卷号:5
  • 期号:3
  • 出版社:Zarqa Private University
  • 摘要:Many problems have emerged while building accurate and efficient clusters of documents; such as the inherent problems of the similarity measure, and document logical view modeling. This research is an attempt to minimize the effect of these problems by using a new definition of transitive relevance between documents; i.e., adding more conditions on transitive relevance judgment through incrementing the relevance threshold by a constant value at each level of transitivity. Proving the relevance relation to be transitive, will make it an equivalence relation that can be used to build equivalence classes of relevant documents. The main contribution of this paper is to use this definition to partition a set of documents into disjoint subsets as equivalence classes (clusters). Another contribution is by using the incremental transitive relevance relation; the traditional vector space model can be made incrementally transitive
  • 关键词:Clustering; equivalence class; information retrieval; incremental transitivity
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