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Improvement and Application of TFIDF Method Based on Text Classification

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2006

Year

Abstract

TFIDF is a kind of common methods used to measure the terms in a document.The method is easy but it undervalues these terms that frequently appear in the documents belonging to the same class,while those terms can represent the characteristic of the documents of this class,so higher weight is entrusted to them.The expression of IDF in TFIDF is modified to increase the weight of those terms mentioned,then is applied to the experiment to validate it.In the experiment,the improved TFIDF is used to select feature and genetic algorithm is used to train the classifier.The method is better than others and proves that the improved TFIDF method is feasible.