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SNDocRank: document ranking based on social networks

9 years 4 months ago
SNDocRank: document ranking based on social networks
To improve the search results for socially-connect users, we propose a ranking framework, Social Network Document Rank (SNDocRank). This framework considers both document contents and the similarity between a searcher and document owners in a social network and uses a Multi-level Actor Similarity (MAS) algorithm to efficiently calculate user similarity in a social network. Our experiment results based on YouTube data show that compared with the tf-idf algorithm, the SNDocRank method returns more relevant documents of interest. Our findings suggest that in this framework, a searcher can improve search by joining larger social networks, having more friends, and connecting larger local communities in a social network. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval
Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolon
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where WWW
Authors Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolong Zhang, C. Lee Giles
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