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http://dx.doi.org/10.3745/KTSDE.2016.5.9.451

Mining Search Keywords for Improving the Accuracy of Entity Search  

Lee, Sun Ku (다음소프트 마이닝랩)
On, Byung-Won (군산대학교 통계컴퓨터과학과)
Jung, Soo-Mok (삼육대학교 컴퓨터학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.5, no.9, 2016 , pp. 451-464 More about this Journal
Abstract
Nowadays, entity search such as Google Product Search and Yahoo Pipes has been in the spotlight. The entity search engines have been used to retrieve web pages relevant with a particular entity. However, if an entity (e.g., Chinatown movie) has various meanings (e.g., Chinatown movies, Chinatown restaurants, and Incheon Chinatown), then the accuracy of the search result will be decreased significantly. To address this problem, in this article, we propose a novel method that quantifies the importance of search queries and then offers the best query for the entity search, based on Frequent Pattern (FP)-Tree, considering the correlation between the entity relevance and the frequency of web pages. According to the experimental results presented in this paper, the proposed method (59% in the average precision) improved the accuracy five times, compared to the traditional query terms (less than 10% in the average precision).
Keywords
Entity Search; FP-Tree; Query; Frequency;
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Times Cited By KSCI : 1  (Citation Analysis)
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