Call For Paper Volume:4 Issue:10 Oct'2017 |

A CONCEPT BASED TEXT MINING AND CLUSTERING FOR SUMMARIZATION

Publication Date : 12/05/2015



Author(s) :

Dr. G. Rasitha Banu MCA., M.Phil., Ph.D., , V.K CHITRA MCA., B.ED..


Volume/Issue :
Volume 2
,
Issue 5
(05 - 2015)



Abstract :

ABSTRACT - Most of the common techniques in text mining are based on the statistical analysis of a term either word or phrase.  Statistical analysis of a term frequency captures the importance of the term within a document only.  However, two terms can have the same frequency in their documents, but one term contributes more to the meaning of its sentences than the other term.  Thus, the underlying text mining model should indicate terms that capture the semantics of text.  In this case, the mining model can capture terms that present the concept of the sentence, which leads to discover the topic of the document. A new concept-based mining model that analyzes terms on the sentence, document, and corpus levels is introduced.  The concept-based mining model can effectively discriminate between non-important terms with respect to sentence semantics and terms which hold the concepts that represent the sentence meaning. The similarity between documents is calculated based on a new concept-based similarity measure.  The proposed similarity measure takes full advantage of using the concept analysis measures on the sentence, document, and corpus level in calculating the similarity between documents. Key Words – Similarity Measures, Clustering Algorithms, Methodology, Implementations and Results


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A CONCEPT BASED TEXT MINING AND CLUSTERING FOR SUMMARIZATION

May 9, 2015