Query-biased Summarization Considering Difference of Paragraphs

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  • Otani Chikara
    Graduate School of Information, Production and Systems, Waseda University
  • Hoo Moon Kyeng
    Software Division, Hitachi, Ltd.
  • Oda Yasushi
    Research Center for Information, Production and Systems, Waseda University
  • Furue Toshihiko
    Environment and Chemistry Engineering Group, Research Laboratory, Kyushu Electric Power Co., Inc.
  • Uchida Yoshitaka
    Environment and Chemistry Engineering Group, Research Laboratory, Kyushu Electric Power Co., Inc.
  • Yoshie Osamu
    Graduate School of Information, Production and Systems, Waseda University

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Other Title
  • パラグラフ間の差異を考慮したｑｕｅｒｙ－ｂｉａｓｅｄな要約手法
  • パラグラフ カン ノ サイ オ コウリョ シタ query biased ナ ヨウヤク シュホウ

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Abstract

Most existing query-biased summarization methods generate the summary using extracted sentences based on similarity measure between all sentences in documents and the query. If there are plural sentences having high similarity to the query in the documents, however, these methods cannot decide from which sentence the summary should be made. This paper proposes an algorithm considering difference of paragraphs, adopting new indicator that shows the difference between one paragraph and the others. In a word space composed of all words in the target document, the algorithm determines the axis that maximizes the difference when a paragraph and the others are projected onto it. There are many combinations of a paragraph and a set of other paragraphs. For each combination, the above-mentioned axis that maximizes the difference and gives a conformity degree to the given query is calculated. With these conformities, the algorithm decides one paragraph for generating the summary. To obtain the axes, topic distinctiveness factor analysis is applied. The basic idea for making final summary is concatenating the sentences extracted from the paragraph. The resultant summary is evaluated from the points of readability, understandability and the easiness to judge whether the link works well or not.

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