• L. Shirisha
• Dr.T.V Rajinikanth
• T.Madhuvani

Day by day the availabilityof text documents are growing in an exponential manner. This growth of text documents throwing challenges to the user and research community in terms of classification. In our paper an attempt was made in finding the keywords in automation way using Rake algorithm on multiple text documents. The Rake algorithm finds more number of Candidate Keywords along with their word scores. In this only stop words was considered. The keywords were sub divided in to High, Middle and low level frequency key words based on word scores and then the similarity measures Jaccard and Euclidean Distance were applied to classify the documents. Comparisons were made among the three approaches High, Middle and low frequency keywords and concluded the results.

TEXT CLASSIFICATION, KEYWORD EXTRACTION, RAKE, SIMILARITY MEASURE

"CLASSIFICATION OF TEXT DOCUMENTS USING JACCARD AND EUCLIDEAN DISTANCE SIMILARITY MEASURES BASED ON WORD SCORES GENERATED BY RAKE ALGORITHM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.339-345, April-2019, Available :http://www.jetir.org/papers/JETIR1904E57.pdf

"CLASSIFICATION OF TEXT DOCUMENTS USING JACCARD AND EUCLIDEAN DISTANCE SIMILARITY MEASURES BASED ON WORD SCORES GENERATED BY RAKE ALGORITHM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp339-345, April-2019, Available at : http://www.jetir.org/papers/JETIR1904E57.pdf