Learning query and document similarities from click-through bipartite graph with metadata

WSDM 2013 - Proceedings of the 6th ACM International Conference on Web Search and Data Mining

Volumn , Issue , 2013, Pages 687-696

  Wu, Wei ^a   Li, Hang ^a,b   Xu, Jun ^a,b  

^a MICROSOFT RESEARCH ASIA   (China)

^b HUAWEI NOAH S ARK LAB   (China)

Author keywords

click through; multi view partial least squares; similarity learning

Indexed keywords

BASELINE METHODS; BIPARTITE GRAPHS; CLICK-THROUGH; DOCUMENT SIMILARITY; ENTERPRISE SEARCHES; FEATURE SPACE; GLOBAL OPTIMUM; GRAPH DATA; HIGH QUALITY; LARGE SCALE EXPERIMENTS; LEARNING PROBLEM; LINEAR COMBINATIONS; LINEAR MAPPING; MULTI-VIEWS; PARTIAL LEAST SQUARE (PLS); RELEVANCE RANKING; SIMILARITY FUNCTIONS; SIMILARITY LEARNING; WEB SEARCHES;

DATA MINING; GRAPH THEORY; INFORMATION RETRIEVAL; SINGULAR VALUE DECOMPOSITION; WEBSITES;

METADATA;

EID: 84874223705     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2433396.2433481     Document Type: Conference Paper

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