XML Documents Clustering Using a Tensor Space Model

نویسندگان

  • Sangeetha Kutty
  • Richi Nayak
  • Yuefeng Li
چکیده

The traditional Vector Space Model (VSM) is not able to represent both the structure and the content of XML documents. This paper introduces a novel method of representing XML documents in a Tensor Space Model (TSM) and then utilizing it for clustering. Empirical analysis shows that the proposed method is scalable for large-sized datasets; as well, the factorized matrices produced from the proposed method help to improve the quality of clusters through the enriched document representation of both structure and content information.

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تاریخ انتشار 2011