人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
論文
検索ログからの半教師あり意味知識獲得の改善
小町 守鈴木 久美
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ジャーナル フリー

2008 年 23 巻 3 号 p. 217-225

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We propose a method for learning semantic categories of words with minimal supervision from web search query logs. Our method is based on the Espresso algorithm (Pantel and Pennacchiotti, 2006) for extracting binary lexical relations, but makes important modifications to handle query log data for the task of acquiring semantic categories. We present experimental results comparing our method with two state-of-the-art minimally supervised lexical knowledge extraction systems using Japanese query log data, and show that our method achieves higher precision than the previously proposed methods.

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© 2008 JSAI (The Japanese Society for Artificial Intelligence)
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