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

• Type: Conference
• Year: 2010
• Where: WWW
• Authors: Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolong Zhang, C. Lee Giles
• Keywords: Actor Similarity, Documents, Internet Technology, Social Networks, WWW 2010