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» Learning to rank for information retrieval (LR4IR 2008)
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WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
14 years 1 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
CIVR
2010
Springer
276views Image Analysis» more  CIVR 2010»
15 years 11 months ago
Optimizing visual search with implicit user feedback in interactive video retrieval
This paper describes an approach to optimize query by visual example results, by combining visual features and implicit user feedback in interactive video retrieval. To this end, ...
Stefanos Vrochidis, Ioannis Kompatsiaris, Ioannis ...
WSDM
2010
ACM
160views Data Mining» more  WSDM 2010»
16 years 3 months ago
Learning Concept Importance Using a Weighted Dependence Model
Modeling query concepts through term dependencies has been shown to have a significant positive effect on retrieval performance, especially for tasks such as web search, where rel...
Michael Bendersky, Donald Metzler, W. Bruce Croft
ADC
2009
Springer
140views Database» more  ADC 2009»
16 years 24 days ago
Score Aggregation Techniques in Retrieval Experimentation
Comparative evaluations of information retrieval systems are based on a number of key premises, including that representative topic sets can be created, that suitable relevance ju...
Sri Devi Ravana, Alistair Moffat
CIKM
2008
Springer
15 years 8 months ago
Efficient and effective link analysis with precomputed salsa maps
SALSA is a link-based ranking algorithm that takes the result set of a query as input, extends the set to include additional neighboring documents in the web graph, and performs a...
Marc Najork, Nick Craswell