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A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization

Thorsten Joachims

出版	School of Computer Science, Carnegie Mellon University, 1996
URL	http://books.google.com.hk/books?id=KHV00AEACAAJ&hl=&source=gbs_api

註釋

Abstract: "A probabilistic analysis of the Rocchio relevance feedback algorithm, one of the most popular learning methods from information retrieval, is presented in a text categorization framework. The analysis results in a probabilistic version of the Rocchio classifier and offers an explanation for the TFIDF word weighting heuristic. The Rocchio classifier, its probabilistic variant and a standard naive Bayes classifier are compared on three text categorization tasks. The results suggest that the probabilistic algorithms are preferable to the heuristic Rocchio classifier."