|
23
|
Discovering key concepts in verbose queries
– M Bendersky, B Croft
- 2009
|
|
10
|
Regression rank: Learning to meet the opportunity of descriptive queries
– M LEASE, J ALLAN, W B CROFT
- 2009
|
|
684
|
A Language Modeling Approach to Information Retrieval
– Jay M. Ponte, W. Bruce Croft
- 1998
|
|
13
|
Analysis of long queries in a large scale search log
– M Bendersky, W B Croft
|
|
142
|
Predicting Query Performance
– Steve Cronen-Townsend, Yun Zhou, W. Bruce Croft
- 2002
|
|
165
|
Improving web search ranking by incorporating user behavior information
– E Agichtein, E Brill, S Dumais
- 2006
|
|
568
|
Optimizing Search Engines using Clickthrough Data
– Thorsten Joachims
- 2002
|
|
124
|
Generating query substitutions
– Rosie Jones, Benjamin Rey, Omid Madani
- 2006
|
|
12
|
A Case for Shorter Queries, and Helping Users Create Them
– Giridhar Kumaran, James Allan
- 2007
|
|
370
|
Okapi at TREC-3
– S.E. Robertson, S. Walker, S. Jones, M.M. Hancock-Beaulieu, M. Gatford
- 1996
|
|
498
|
A Study of Smoothing Methods for Language Models Applied to Ad Hoc Information Retrieval
– Chengxiang Zhai, John Lafferty
|
|
97
|
Relevance based language models
– V Lavrenko, W B Croft
- 2001
|
|
46
|
Inferring query performance using pre-retrieval predictors
– Ben He, Iadh Ounis
- 2004
|
|
103
|
A Markov Random Field Model for Term Dependencies
– Donald Metzler Metzler
- 2004
|
|
14
|
Learning noun phrase query segmentation
– S Bergsma, Q I Wang
- 2007
|
|
2
|
Predicting query performance on the web
– N Balasubramanian, G Kumaran, V R Carvalho
- 2010
|
|
14
|
Improved query difficulty prediction for the web
– C Hauff, V Murdock, R Baeza-Yates
|
|
70
|
M: Classification and regression by randomForest
– A Liaw, Wiener
|
|
76
|
Q.: Learning to rank with nonsmooth cost functions
– C Burges, R Ragno, Le
- 2007
|
