Ranking specialization for web search: A divide-and-conquer approach by using topical RankSVM

Proceedings of the 19th International Conference on World Wide Web, WWW '10

Volumn , Issue , 2010, Pages 131-140

  Bian, Jiang ^a   Li, Xin ^b   Li, Fan ^b   Zheng, Zhaohui ^b   Zha, Hongyuan ^a  

^a Georgia Institute of Technology   (United States)

^b YAHOO RESEARCH   (United States)

Author keywords

ranking specialization for web search; ranking sensitive query topic; topical RankSVM

Indexed keywords

BENCHMARK DATASETS; DATA SETS; DIVIDE AND CONQUER; DIVIDE-AND-CONQUER APPROACH; LEARNING PROCESS; LOSS FUNCTIONS; MACHINE LEARNING TECHNIQUES; MODEL APPROACH; RANKING ALGORITHM; RANKING APPROACH; RANKING FUNCTIONS; RANKING MODEL; RANKING PERFORMANCE; UNSUPERVISED CLUSTERING METHODS; WEB SEARCHES;

INFORMATION RETRIEVAL; LEARNING ALGORITHMS; SEARCH ENGINES;

WORLD WIDE WEB;

EID: 77954655724     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1772690.1772705     Document Type: Conference Paper

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