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Full Version: Text summarization based on sentences clustering and extraction
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Text summarization is a process of reducing the size of a text while preserving its information content. Automatic text summarization aims to address the information overload problem by extracting the most important information from a document. Traditional method of summarization uses the sentence features to evaluate the importance of sentences of a document. Its limitation is it is not involved with the sentence semantic similarity computing. This project proposes a summarization approach based on sentence semantic similarity computing and sentences clustering. The purpose of this project is to show that summarization result is not only depends on the sentence features, but also depends on the sentence similarity measure.