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As an emerging area in information retrieval, question answering aims at retrieving answers to user-posted questions from a given sentence collection or text corpus. In question answering, the queries are usually submitted in the form of short sentences which are unable to represent user intentions sufficiently. In this study, we present a novel framework which improves question answering through...
Feature selection is an important task for text categorization. Traditional feature selection methods are based on terms but they may lose some useful information in texts. In this paper, we present a feature selection method that considers not only general terms but also named entities. Corresponding to our feature selection method, we propose a term weighting scheme for named entities. The experiments...
Term weighting is an important task for text classification. Inverse document frequency (IDF) is one of the most popular methods for this task; however, in some situations, such as supervised learning for text categorization, it doesn 't weight terms properly, because it neglects the category information and assumes that a term that occurs in smaller set of documents should get a higher weight. There...
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