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- W19458567 abstract "This paper provides a solution to the issue: “How can we use Wikipedia based concepts in documentclustering with lesser human involvement, accompanied by effective improvements in result?” In thedevised system, we propose a method to exploit the importance of N-grams in a document and useWikipedia based additional knowledge for GAAC based document clustering. The importance of N-gramsin a document depends on several features including, but not limited to: frequency, position of theiroccurrence in a sentence and the position of the sentence in which they occur, in the document. First, weintroduce a new similarity measure, which takes the weighted N-gram importance into account, in thecalculation of similarity measure while performing document clustering. As a result, the chances of topical similarity in clustering are improved. Second, we use Wikipedia as an additional knowledge base both, to remove noisy entries from the extracted N-grams and to reduce the information gap between N-grams that are conceptually-related, which do not have a match owing to differences in writing scheme or strategies. Our experimental results on the publicly available text dataset clearly show that our devised system has a significant improvement in performance over bag-of-words based state-of-the-art systems in this area." @default.
- W19458567 created "2016-06-24" @default.
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- W19458567 date "2010-10-25" @default.
- W19458567 modified "2023-09-27" @default.
- W19458567 title "EXPLOITING N-GRAM IMPORTANCE AND ADDITIONAL KNOWEDGE BASED ON WIKIPEDIA FOR IMPROVEMENTS IN GAAC BASED DOCUMENT CLUSTERING" @default.
- W19458567 hasPublicationYear "2010" @default.
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