A kernel approach to addressing term mismatch

Proceedings of the 20th International Conference Companion on World Wide Web, WWW 2011

Volumn , Issue , 2011, Pages 153-154

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

^a MICROSOFT RESEARCH ASIA   (China)

^b PEKING UNIVERSITY   (China)

Author keywords

blending; click through data; kernel methods; term mismatch

Indexed keywords

BASELINE METHODS; CLICK-THROUGH DATA; DATA SETS; DOCUMENT SIMILARITY; ENTERPRISE SEARCHES; KERNEL APPROACHES; KERNEL METHODS; LARGE SCALE EXPERIMENTS; MISMATCH PROBLEMS; MIXTURE MODEL; MODEL-BASED; QUERY EXPANSION; QUERY SIMILARITY; TERM MISMATCH; WEB SEARCHES;

BLENDING; HEURISTIC METHODS; INFORMATION RETRIEVAL;

WORLD WIDE WEB;

EID: 79955143094     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1963192.1963270     Document Type: Conference Paper

References (5)

1. R. A. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1999.
2. N. J. Belkin, C. Cool, W. B. Croft, and J. P. Callan. The effect multiple query representations on information retrieval system performance. In SIGIR '93, pages 339-346, 1993.
3. T. Joachims. Optimizing search engines using clickthrough data. In SIGKDD '02, pages 133-142, 2002.
4. B. Schölkopf and A. Smola. Learning with kernels: Support vector machines, regularization, optimization, and beyond. MIT Press, 2002.
5. W. Wu, J. Xu, H. Li, and S. Oyama. Asymmetric Kernel Learning Microsoft Technical Report, MSR-TR-2010-85, 2010.