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The main objective of this work is to classify Hindi stories into three genres: fable, folk-tale and legend. In this paper, we are proposing a framework for story classification using keyword and Part-of-speech (POS) based features. Keyword based features like Term Frequency (TF) and Term Frequency Inverse Document
Current search engines have two problems, losing useful information and including useless information. These two problems are aroused by the keyword matching retrieval model, which is adopted by almost all search engines. We introduce the conception of category attribute of a word. According to the category attribute
of cultural information. Therefore, text categorization research has become more important. The paper improved the precision of the traditional text categorization by the process that we mended the weight of words and mined potential keywords, then found their relationship. In the end of the paper, an experiment was
the current Web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. So this paper present a algorithm of Chinese text classification on semantic Web. After getting keywords from the Web text, we get rid of ambiguity of the keywords. Then we get the semantic
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