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» Listwise approach to learning to rank: theory and algorithm
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CIKM
2005
Springer
13 years 11 months ago
Using RankBoost to compare retrieval systems
This paper presents a new pooling method for constructing the assessment sets used in the evaluation of retrieval systems. Our proposal is based on RankBoost, a machine learning v...
Huyen-Trang Vu, Patrick Gallinari
JUCS
2010
217views more  JUCS 2010»
13 years 7 months ago
The 3A Personalized, Contextual and Relation-based Recommender System
Abstract: This paper discusses the 3A recommender system that targets CSCL (computersupported collaborative learning) and CSCW (computer-supported collaborative work) environments....
Sandy El Helou, Christophe Salzmann, Denis Gillet
ROCAI
2004
Springer
14 years 2 months ago
Learning Interestingness Measures in Terminology Extraction. A ROC-based approach
Abstract. In the field of Text Mining, a key phase in data preparation is concerned with the extraction of terms, i.e. collocation of words attached to specific concepts (e.g. Ph...
Mathieu Roche, Jérôme Azé, Yve...
TREC
2003
13 years 10 months ago
Ranking Function Discovery by Genetic Programming for Robust Retrieval
Ranking functions are instrumental for the success of an information retrieval (search engine) system. However nearly all existing ranking functions are manually designed based on...
Li Wang, Weiguo Fan, Rui Yang, Wensi Xi, Ming Luo,...
CIKM
2008
Springer
13 years 11 months ago
Trada: tree based ranking function adaptation
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...