Correlation Preserving Indexing Based Text Clustering

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2013, Vol 13, Issue 1

Abstract

 In Document clustering previously they presented new document clustering method based on correlation preserving indexing. It simultaneously maximizes the correlation between the documents in the  local patches and minimizes the correlation between the documents outside these patches. Consequently, a low  dimensional semantic subspace is derived where the documents corresponding to the same semantics are close  to each other with learning level parsing procedure based CPI method. The proposed CPI method with learning  level parsing procedure is to find correlation between relational documents to avoid maximum unknown  clusters those are not effectual to find exact correlation between documents depend on accuracy of sentences.  The proposed CPI method with learning level parsing procedure in document clustering doubles the accuracy of  previous correlation coefficient. The proposed hierarchical clustering algorithm behavior is different with CPI  in terms of NMI, Accuracy

Authors and Affiliations

Venkata Gopala Rao . S

Keywords

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  • EP ID EP87638
  • DOI -
  • Views 168
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How To Cite

Venkata Gopala Rao . S (2013).  Correlation Preserving Indexing Based Text Clustering. IOSR Journals (IOSR Journal of Computer Engineering), 13(1), 27-30. https://europub.co.uk/articles/-A-87638