Multi-task learning to rank for web search

Pattern Recognition Letters

Volumn 33, Issue 2, 2012, Pages 173-181

  Chang, Yi ^a   Bai, Jing ^b   Zhou, Ke ^c   Xue, Gui Rong ^d,e   Zha, Hongyuan ^c   Zheng, Zhaohui ^a  

^a YAHOO RESEARCH   (United States)

^b MICROSOFT   (United States)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^d SHANGHAI JIAO TONG UNIVERSITY   (China)

^e Aliyun Cloud Computing ^*  (China)

Author keywords

Convergence analysis; Learning to rank; Multi task learning; Non parametric common structure

Indexed keywords

BASELINE METHODS; COMMON STRUCTURES; CONVERGENCE ANALYSIS; DIFFERENT DOMAINS; GLOBAL SEARCH; LEARNING TO RANK; LINEAR COMBINATIONS; MULTI-TASK LEARNING; MULTIPLE DOMAINS; MULTIPLE TASKS; NON-PARAMETRIC; NON-PARAMETRIC COMMON STRUCTURE; RANK FUNCTIONS; RANKING FUNCTIONS; REGRESSION FUNCTION; SEARCH RESULTS; SIGNIFICANT IMPACTS; TRAINING DATA; WEB SEARCHES;

INFORMATION RETRIEVAL; LEARNING SYSTEMS; SEARCH ENGINES;

WORLD WIDE WEB;

EID: 81055138158     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2011.09.020     Document Type: Article

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