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Volume & Issue no: Volume 5, Issue 6, November - December 2016

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Title:
SIMILARITY MEASURE FOR TEXT CLASSIFICATION
Author Name:
Radha mothukuri, Nagaraju.M, Divya Chilukuri
Abstract:
Abstract Text processing plays very important role in information retrieval, data mining and web search. Text classification can efficiently enhance the text processing capability by automatically sorting out them according to defined collection of categories. Measuring the similarity between documents is an important operation in the text processing field. In this work, a similarity measure is proposed to compute the similarity between two documents with respect to a feature. The proposed measure takes the following three cases into account: The feature appears in both documents, the feature appears in only one document, and the feature appears in none of the documents. For the first case, the similarity increases as the difference between the two involved feature values decreases. Furthermore, the contribution of the difference is normally scaled. For the second case, a fixed value is contributed to the similarity. For the last case, the feature has no contribution to the similarity. The proposed measure will be extended to gauge the similarity between two sets of documents. The effectiveness of this measure will be evaluated on several real-world data sets for text classification problems. Keywords:-text mining, classification, similarity measure,accuracy.
Cite this article:
Radha mothukuri, Nagaraju.M, Divya Chilukuri , " SIMILARITY MEASURE FOR TEXT CLASSIFICATION" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 5, Issue 6, November - December 2016 , pp. 016-024 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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