Topic Keyword Identification for Text Summarization Using Lexical Clustering(Special Issue on Text Processing for Information Access)

概要

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Automatic text summarization has the goal of reducing the size of a document while preserving its content. Generally, producing a summary as extracts is achieved by including only sentences which are the most topic-related. DOCUSUM is our summarization system based on a new topic keyword identification method. The process of DOCUSUM is as follows. First, DOCUSUM converts the content words of a document into elements of context vector space. It then constructs lexical clusters from the context vector space and identifies core clusters. Next, it selects topic keywords from the core clusters. Finally, it generates a summary of the document using the topic keywords. In the experiments on various compression ratios (the compression of 30%, the compression of 10%, and the extraction of the fixed number of sentences : 4 or 8 sentences), DOCUSUM showed better performance than other methods.
一般社団法人電子情報通信学会の論文
2003-09-01