A Fuzzy Improved Weighted Tree Analysis Approach for Document Clustering |
Author(s): |
| Sangeeta Yadav , PDM College of Engineering & Technology; Dr. Yusuf Mulge, PDM College of Engineering & Technology; Mr. Ajay Dureja, PDM College of Engineering & Technology |
Keywords: |
| Fuzzy Improved Weighted Tree, Document Clustering |
Abstract |
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Document clustering is the process dividing the document into groups or clusters. The similar objects are classified into one group and dissimilar into other group. It is an unsupervised learning process. This paper proposes a fuzzy improved weighted tree analysis approach based on fuzzy rules and a two stage algorithm. At the first stage, the documents are summarized. At this stage the document filtration as well as document statistics will be collected. At the second stage the documents are classified. In this stage the statistical analysis will be performed based on correlation analysis, entropy analysis and frequency measure. The fuzzy rules are applied on all this parameters and adaptive document category will be identified. At this stage, a weighted tree based approach will be applied for document clustering. |
Other Details |
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Paper ID: IJSRDV3I50501 Published in: Volume : 3, Issue : 5 Publication Date: 01/08/2015 Page(s): 904-907 |
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