Giving temporal order to news corpus

  • Authors:
  • Hiroshi Uejima;Takao Miura;Isamu Shioya

  • Affiliations:
  • Dept. of Elect. & Elect. Engr., HOSEI University, Tokyo, Japan;Dept. of Elect. & Elect. Engr., HOSEI University, Tokyo, Japan;Dept. of Management and Informatics, SANNO University, Kanagawa, Japan

  • Venue:
  • CIS'04 Proceedings of the First international conference on Computational and Information Science
  • Year:
  • 2004

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Abstract

In this investigation, we propose a new mechanism to give temporal order to a news article in a form of timestamps. Here we learn temporal data in advance to extract ordering by means of incremental clustering and then we estimate most likely order to news text. In this work, we examine TDT2 corpus and we show how well our approach works by some experiments.