Abstract
Social networks (e.g., Facebook, Twitter) have attracted significant attention recently. Many users have a search requirement to find new or existing friendships with similar interests in social networks. A well-known computing model is keyword search, which provides a user-friendly interface to meet users search demands. However traditional keyword search techniques only consider the textual proximity and ignore the relationship closeness between different users. It is a big challenge to integrate social relationship and textual proximity and it calls for an effective method to support keyword search in social networks. To address these challenges, we present a tree decomposition based hierarchical keyword index structure (TDK-Index) to solve the problem. Our major contributions are: (1)TDK-Index which integrate keyword index and relationship closeness index as a whole; (2)Two-phase TA algorithm which narrows the threshold obviously compared to existing methods and speed up top-k query by a factor of two; and (3)flexible solution which adopts different application circumstances by parameter adjustment. Our experiments provide evidences of the efficiency and scalability of our solution.
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Du, X. (2012). An Efficient Index for Top-k Keyword Search on Social Networks. In: Gao, H., Lim, L., Wang, W., Li, C., Chen, L. (eds) Web-Age Information Management. WAIM 2012. Lecture Notes in Computer Science, vol 7418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32281-5_43
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DOI: https://doi.org/10.1007/978-3-642-32281-5_43
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