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Detection of Difference between News Articles on the Same Topic Based on Sequential Comparison

Tomoya Noro Takehiro Tokuda

刊行年
2010-01-01
収録
『Frontiers in artificial intelligence and applications』
言語
英語
OpenAlex
W2172539232
DOI
10.3233/978-1-60750-477-1-59
MAG
2172539232
ISSN
0922-6389
URL
https://doi.org/10.3233/978-1-60750-477-1-59

要旨

Currently, a lot of news articles are published on the Web, and it is getting easier for us to read them. However, the number of articles are too large for us to read all of them. Although some Web sites cluster/classify news articles into some topics (categories), it is not enough since a large number of articles are still in each topic. Detecting difference between articles on one topic will be one of the solution to comprehend the whole topic. In this paper, we propose a method for detection of difference between news articles on the same topic. Articles are sequentially compared by three different comparison units: paragraphs, sentences, and simple sentences. Our method is evaluated by applying it to Japanese news articles.

主題

この書誌の出所

  • openalex— W2172539232(2026-08-14取得)

引用

Tomoya Noro・Takehiro Tokuda(2010-01-01) Detection of Difference between News Articles on the Same Topic Based on Sequential Comparison 『Frontiers in artificial intelligence and applications』

NoroTokuda2010DetectionDifferenceBetween
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