A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
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发表时间：
1997-07
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通讯作者：
T. Joachims
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作者：
T. Joachims
摘要：在文本分类框架下，对信息检索中最流行的学习方法之一Rocchio相关反馈算法进行了概率分析。的分析结果在概率版本的Rocchio分类，并提供了一个解释TFIDF字加权启发式。Rocchio分类器，它的概率变体和一个标准的朴素贝叶斯分类器进行了比较，在三个文本分类任务。结果表明，概率算法优于启发式Rocchio分类器。
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.