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» A General Language Model for Information Retrieval
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CIKM
2011
Springer
14 years 4 months ago
A probabilistic method for inferring preferences from clicks
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke
WWW
2009
ACM
16 years 5 months ago
Search result re-ranking based on gap between search queries and social tags
Both search engine click-through log and social annotation have been utilized as user feedback for search result re-ranking. However, to our best knowledge, no previous study has ...
Jun Yan, Ning Liu, Elaine Qing Chang, Lei Ji, Zhen...
WWW
2007
ACM
16 years 5 months ago
Supervised rank aggregation
This paper is concerned with rank aggregation, the task of combining the ranking results of individual rankers at meta-search. Previously, rank aggregation was performed mainly by...
Yu-Ting Liu, Tie-Yan Liu, Tao Qin, Zhiming Ma, Han...
JCDL
2010
ACM
184views Education» more  JCDL 2010»
15 years 9 months ago
Evaluating topic models for digital libraries
Topic models could have a huge impact on improving the ways users find and discover content in digital libraries and search interfaces, through their ability to automatically lea...
David Newman, Youn Noh, Edmund M. Talley, Sarvnaz ...
WIDM
2005
ACM
15 years 10 months ago
Web path recommendations based on page ranking and Markov models
Markov models have been widely used for modelling users' navigational behaviour in the Web graph, using the transitional probabilities between web pages, as recorded in the w...
Magdalini Eirinaki, Michalis Vazirgiannis, Dimitri...