Mining Search Keywords for Improving the Accuracy of Entity Search


KIPS Transactions on Software and Data Engineering, Vol. 5, No. 9, pp. 451-464, Sep. 2016
10.3745/KTSDE.2016.5.9.451,   PDF Download:
Keywords: Entity Search, FP-Tree, Query, frequency
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).


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Cite this article
[IEEE Style]
L. S. Ku, O. Byung-Won, J. Soo-Mok, "Mining Search Keywords for Improving the Accuracy of Entity Search," KIPS Transactions on Software and Data Engineering, vol. 5, no. 9, pp. 451-464, 2016. DOI: 10.3745/KTSDE.2016.5.9.451.

[ACM Style]
Lee Sun Ku, On Byung-Won, and Jung Soo-Mok. 2016. Mining Search Keywords for Improving the Accuracy of Entity Search. KIPS Transactions on Software and Data Engineering, 5, 9, (2016), 451-464. DOI: 10.3745/KTSDE.2016.5.9.451.