N-33 Topic Extraction and Summarization in News Archive using TF^*PDF Algorithm and Sentence Vector Clustering

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概要

• 論文の詳細を見る

• Busy and no time to digest the news archive .... ? Ever since the Web wide-spreading, the amount of electronically available information online, especially news archive proliferates and threatens to overwhelm human attention. Seeing this, we propose an information system that will extract the main topics in the news archive in a weekly basis. By getting a weekly report, user can know what were the main news events in the past week.

• FIT(電子情報通信学会・情報処理学会)推進委員会の論文
• 2002-09-13

著者

• Ishizuka Mitsuru

  Dept. Of Info. & Comm. Eng. The University Of Tokyo

• Bun Khoo

  Dept. Of Info. & Comm. Eng. The University Of Tokyo

• Dohi Hiroshi

  Dept. of Info. & Comm. Eng., The University of Tokyo

• Dohi Hiroshi

  Dept. Of Info. & Comm. Eng. The University Of Tokyo

関連論文

• A Two-Model Framework for Multimodal Presentation with Life-like Characters in Flash Medium
• N-33 Topic Extraction and Summarization in News Archive using TF^*PDF Algorithm and Sentence Vector Clustering
• 4Y-9 Coalition among Information Agent Based on Cost Model(情報システムの構築(1),一般講演,コンピュータと人間社会)
• Push Mode of Change and Difference Information on the Web Based on Agent Interaction (特集 知識流通)
• A Two-Model Framework for Multimodal Presentation with Life-like Characters in Flash Medium (特集 エージェント (合同研究会)人工知能学会知識ベースシステム研究会,情報処理学会知能と複雑系研究会 Joint Agent Workshops & Symposium (JAWS 2003))

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