Personalized and Social Search by Finding User Similarity based on Social Networks


KIPS Transactions on Software and Data Engineering, Vol. 16, No. 5, pp. 683-690, May. 2009
10.3745/KIPSTD.2009.16.5.683, Full Text:

Abstract

Social Networks which is composed of network with an individual in the center in a web support mutual-understanding of information by searching user profile and forming new link. Therefore, if we apply the Social Network which consists of web users who have similar immanent information to web search, we can improve efficiency of web search and satisfaction of web user about search results. In this paper, first, we make a Social Network using web users linked directly or indirectly. Next, we calculate Similarity among web users using their immanent information according to topics, and then reconstruct Social Network based on varying Similarity according to topics. Last, we compare Similarity with Search Pattern. As a result of this test, we can confirm a result that among users who have high relationship index, that is, who have strong link strength according to personal attributes have similar search pattern. If such fact is applied to search algorithm, it can be possible to improve search efficiency and reliability in personalized and social search.


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Cite this article
[IEEE Style]
G. W. Park, J. W. Oh and S. H. Lee, "Personalized and Social Search by Finding User Similarity based on Social Networks," KIPS Journal D (2001 ~ 2012) , vol. 16, no. 5, pp. 683-690, 2009. DOI: 10.3745/KIPSTD.2009.16.5.683.

[ACM Style]
Gun Woo Park, Jung Woon Oh, and Sang Hoon Lee. 2009. Personalized and Social Search by Finding User Similarity based on Social Networks. KIPS Journal D (2001 ~ 2012) , 16, 5, (2009), 683-690. DOI: 10.3745/KIPSTD.2009.16.5.683.