Sentence Extraction by Spreading Activation through Sentence Similarity

Naoaki Okazaki, Yutaka Matsuo, Naohiro Matsumura, Mitsuru Ishizuka

研究成果: Article査読

18 被引用数 (Scopus)

抄録

Although there has been a great deal of research on automatic summarization, most methods rely on statistical methods, disregarding relationships between extracted textual segments. We propose a novel method to extract a set of comprehensible sentences which centers on several key points to ensure sentence connectivity. It features a similarity network from documents with a lexical dictionary, and spreading activation to rank sentences. We show evaluation results of a multi-document summarization system based on the method participating in a competition of summarization, TSC (Text Summarization Challenge) task, organized by the third NTCIR project.

本文言語English
ページ(範囲)1686-1694
ページ数9
ジャーナルIEICE Transactions on Information and Systems
E86-D
9
出版ステータスPublished - 2003 9
外部発表はい

ASJC Scopus subject areas

  • 情報システム
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • ソフトウェア

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