SNDocRank: A social network-based video search ranking framework

Liang Gou, Hung Hsuan Chen, Jung Hyun Kim, Xiaolong Zhang, C. Lee Giles

研究成果: 書貢獻/報告類型會議論文篇章同行評審

15 引文 斯高帕斯(Scopus)

摘要

Multimedia ranking algorithms are usually user-neutral and measure the importance and relevance of documents by only using the visual contents and meta-data. However, users' interests and preferences are often diverse, and may demand different results even with the same queries. How can we integrate user interests in ranking algorithms to improve search results? Here, we introduce Social Network Document Rank (SNDocRank), a new ranking framework that considers a searcher's social network, and apply it to video search. SNDocRank integrates traditional tf-idf ranking with our Multi-level Actor Similarity (MAS) algorithm, which measures the similarity between social networks of a searcher and document owners. Results from our evaluation study with a social network and video data from YouTube show that SNDocRank offers search results more relevant to user's interests than other traditional ranking methods.

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主出版物標題MIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval
頁面367-376
頁數10
DOIs
出版狀態已出版 - 2010
事件2010 ACM SIGMM International Conference on Multimedia Information Retrieval, MIR 2010 - Philadelphia, PA, United States
持續時間: 29 3月 201031 3月 2010

出版系列

名字MIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval

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???event.eventtypes.event.conference???2010 ACM SIGMM International Conference on Multimedia Information Retrieval, MIR 2010
國家/地區United States
城市Philadelphia, PA
期間29/03/1031/03/10

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