Sentence Extraction by Spreading Activation through Sentence Similarity(Special Issue on Text Processing for Information Access)

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概要

• 論文の詳細を見る

• 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.

• 社団法人電子情報通信学会の論文
• 2003-09-01

著者

• Ishizuka Mitsuru

  Graduate School Of Information Science And Technology The University Of Tokyo

• Matsuo Yutaka

  Cyber Assist Research Center Aist Tokyo Waterfront

• OKAZAKI Naoaki

  Graduate School of Information Science and Technology, The University of Tokyo

• MATSUMURA Naohiro

  Graduate School of Information Science and Technology, The University of Tokyo

• Okazaki Naoaki

  Graduate School Of Information Science And Technology The University Of Tokyo

• Matsumura Naohiro

  Graduate School Of Information Science And Technology The University Of Tokyo

関連論文

• Sentence Extraction by Spreading Activation through Sentence Similarity(Special Issue on Text Processing for Information Access)

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