著者

小町 守 鈴木 久美

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.23, no.3, pp.217-225, 2008 (Released:2008-03-11)

参考文献数

16

被引用文献数

3 6

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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.