An Efficient Semantic Model For Concept Based Clustering And Classification
Journal Title: International Journal on Computer Science and Engineering - Year 2012, Vol 4, Issue 3
Abstract
Usually in text mining techniques the basic measures like term frequency of a term (word or phrase) is computed to compute the importance of the term in the document. But with statistical analysis, the original semantics of the term may not carry the exact meaning of the term. To overcome this problem, a new framework has been introduced which relies on concept based model and synonym based approach. The proposed model can efficiently find significant matching and related concepts between documents according to concept based and synonym based approaches. Large sets of experiments using the proposed model on different set in clustering and classification are conducted. Experimental results demonstrate the substantial enhancement of the clustering quality using sentence based, document based, corpus based and combined approach concept analysis. A new similarity measure has been proposed to find the similarity between a document and the existing clusters, which can be used in classification of the document with existing clusters.
Authors and Affiliations
SaiSindhu Bandaru , Dr. K B Madhuri
Keywords
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