Query Likelihood Model
Query Likelihood Model is a probabilistic retrieval model that ranks documents based on the likelihood of a query being generated from their language model, typically estimated using maximum likelihood or smoothed probability distributions.
36
Publications
2.9K
Citations
92
Authors
41
Institutions
Publications per year
2017–2026
8
36
Retrieval models for question and answer archives
Xiaobing Xue, Jiwoon Jeon, W. Bruce Croft · 2008 · 371 citations
Xiaoyan Li, W. Bruce Croft · 2003 · 272 citations
Estimation methods for ranking recent information
Miles Efron, Gene Golovchinsky · 2011 · 113 citations
Towards query log based personalization using topic models
Mark Carman, Fábio Crestani, Morgan Harvey et al. · 2010 · 77 citations
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University of Massachusetts Amherst
Amherst Center, United States
5 h-index
10 publications
1.2K citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
12 publications
462 citations
Institute of Computing Technology
Beijing, China
3 h-index
12 publications
462 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
4 publications
230 citations

University of Glasgow
Glasgow, United Kingdom
2 h-index
4 publications
122 citations
University of Massachusetts Boston
Boston, United States
2 h-index
4 publications
592 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
3 publications
81 citations

University of Amsterdam
Amsterdam, The Netherlands
2 h-index
3 publications
42 citations
1–8 of 41
3 publications · 1.3K citations
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Repository · 2 publications · 37 citations
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1 publications · 38 citations
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Repository · 1 publications · 19 citations
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JIS · 1 publications · 22 citations
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