Estimating query performance using class predictions

Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009

Volumn , Issue , 2009, Pages 672-673

  Collins Thompson, Kevyn ^a   Bennett, Paul N ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

Query difficulty; Text classification

Indexed keywords

CLASS INFORMATION; CLASS PREDICTION; CLASS-BASED; COMPUTATION OVERHEADS; EMPIRICAL STUDIES; LANGUAGE MODEL; PRECOMPUTE; QUALITY MEASURES; QUERY PERFORMANCE; SEARCH RESULTS; TEXT CLASSIFICATION;

COMPUTATIONAL LINGUISTICS; COMPUTER CRIME; FORECASTING; INFORMATION RETRIEVAL; INFORMATION SERVICES; PACKET NETWORKS; RISK PERCEPTION;

TEXT PROCESSING;

EID: 72449169582     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1571941.1572071     Document Type: Conference Paper

References (10)

1. B. Billerbeck. Efficient Query Expansion. PhD thesis, RMIT University, Melbourne, Australia, 2005.
2. A. Broder, M. Ciaramita, M. Fontoura, E. Gabrilovich, V. Josifovski, D. Metzler, V. Murdock, and V. Plachouras. To swing or not to swing: learning when (not) to advertise. In CIKM '08, pages 1003-1012.
3. S. Cronen-Townsend and W. Croft. Quantifying query ambiguity. In Proceedings of HCL 2002, pages 94-98, 2002.
4. C. Hauff, V. Murdock, and R. Baeza-Yates. Improved query difficulty prediction for the web. In CIKM '08, pages 439-448.
5. B. He and I. Ounis. Query performance prediction. Information Systems, 31:585-594, 2006.
6. Netscape Communication Corporation. Open directory project. http://www.dmoz.org.
7. G. Qiu, K. Liu, J. Bu, C. Chen, and Z. Kang. Quantify query ambiguity using ODP metadata. In SIGIR '07, pages 697-698.
8. R. Song, Z. Luo, J.-R. Wen, Y. Yu, and H.-W. Hon. Identifying ambiguous queries in web search. In WWW '07.
9. M. Winaver, O. Kurland, and C. Domshlak. Towards robust query expansion: model selection in the language modeling framework. In SIGIR '07, pages 729-730.
10. Y. Zhou and W. B. Croft. Ranking robustness: a novel framework to predict query performance. In CIKM 2006.