Giving Temporal Order to News Corpus

Authors:
Hiroshi Uejima;Takao Miura;Isamu Shioya
Affiliations:
Hosei University;Hosei University;Sanno University
Venue:
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Year:
2004

Citing 0
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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 vorpus and we show how well our approach works by some experiments.