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» Learning to rank for information retrieval
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WWW
2009
ACM
14 years 8 months ago
A dynamic bayesian network click model for web search ranking
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...
Olivier Chapelle, Ya Zhang
RECSYS
2009
ACM
14 years 2 months ago
Collaborative prediction and ranking with non-random missing data
A fundamental aspect of rating-based recommender systems is the observation process, the process by which users choose the items they rate. Nearly all research on collaborative ï¬...
Benjamin M. Marlin, Richard S. Zemel
ECIR
2009
Springer
14 years 4 months ago
Risk-Aware Information Retrieval
Probabilistic retrieval models usually rank documents based on a scalar quantity. However, such models lack any estimate for the uncertainty associated with a document’s rank. Fu...
Jianhan Zhu, Jun Wang, Michael J. Taylor, Ingemar ...
TREC
2004
13 years 9 months ago
Novel Approaches in Text Information Retrieval - Experiments in the Web Track of TREC 2004
: In this paper, we report our experiments in the mixed query task of the Web track for TREC 2004. We deal with the problem of ranking Web documents within a multicriteria framewor...
Mohamed Farah, Daniel Vanderpooten
TKDE
2002
121views more  TKDE 2002»
13 years 7 months ago
ACIRD: Intelligent Internet Document Organization and Retrieval
This paper presents an intelligent Internet information system, Automatic Classifier for the Internet Resource Discovery (ACIRD), which uses machine learning techniques to organiz...
Shian-Hua Lin, Meng Chang Chen, Jan-Ming Ho, Yueh-...