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Vol.23 No.1
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An Experimental Study on Automatic Summarization of Multiple News Articles

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2006, v.23 no.1, pp.83-98
https://doi.org/10.3743/KOSIM.2006.23.1.083


& (2006). An Experimental Study on Automatic Summarization of Multiple News Articles. Journal of the Korean Society for Information Management, 23(1), 83-98, https://doi.org/10.3743/KOSIM.2006.23.1.083
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Abstract

This study proposes a template-based method of automatic summarization of multiple news articles using the semantic categories of sentences. First, the semantic categories for core information to be included in a summary are identified from training set of documents and their summaries. Then, cue words for each slot of the template are selected for later classification of news sentences into relevant slots. When a news article is input, its event/accident category is identified, and key sentences are extracted from the news article and filled in the relevant slots. The template filled with simple sentences rather than original long sentences is used to generate a summary for an event/accident. In the user evaluation of the generated summaries, the results showed the 54.1% recall ratio and the 58.1% precision ratio in essential information extraction and 11.6% redundancy ratio.

keywords
복수문헌 자동요약, 뉴스기사 자동요약, 템플리트, 슬롯 단서어, 의미범주, multi-document summarization, news article summarization, template, slot cue word, semantic category, multi-document summarization, news article summarization, template, slot cue word, semantic category

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