551 search results - page 22 / 111 » Learning to rank for information retrieval (LR4IR 2008) |
184
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ICML
2007
IEEE
16 years 6 months ago
2007
IEEE
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
175
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WWW
2008
ACM
16 years 6 months ago
2008
ACM
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
180
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CIKM
2009
Springer
16 years 20 days ago
2009
Springer
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
163
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SIGIR
2004
ACM
15 years 11 months ago
2004
ACM
This paper proposes a novel, unified, and systematic approach to combine collaborative and content-based filtering for ranking and user preference prediction. The framework inco...
207
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SIGIR
2011
ACM
14 years 9 months ago
2011
ACM
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...