Learning to rank audience for behavioral targeting

SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2010, Pages 719-720

  Liu, Ning ^a   Yan, Jun ^a   Shen, Dou ^b   Chen, Depin ^c   Chen, Zheng ^a   Li, Ying ^b  

^a MICROSOFT RESEARCH ASIA   (China)

^b MICROSOFT   (United States)

^c UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Behavioral targeting; Learning to rank; Online advertising

Indexed keywords

BEHAVIORAL TARGETING; CLICK-THROUGH; LEARNING TO RANK; ONLINE ADVERTISING; RECENT TRENDS; SEARCH QUERIES; USER BEHAVIORS; USER SEGMENT;

INFORMATION RETRIEVAL; SEARCH ENGINES;

FEATURE EXTRACTION;

EID: 77956050440     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1835449.1835582     Document Type: Conference Paper

References (2)

1. J. Yan, N. Liu, G. Wang, W. Zhang, Y. Jiang, and Z. Chen. How much behavioral targeting help online advertising? In Proceedings of the 18th International World Wide Web Conference (WWW), 2009.
2. R. Herbrich, T. Graepel, and K. Obermayer. Large margin rank boundaries for ordinal regression. In Advances in Large Margin Classifiers, MA, MIT Press, 2000.