395 search results - page 16 / 79 » Learning to rank with partially-labeled data |
KDD
2005
ACM
16 years 4 days ago
2005
ACM
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
CIKM
2000
Springer
15 years 4 months ago
2000
Springer
RankBoost is a recently proposed algorithm for learning ranking functions. It is simple to implement and has strong justifications from computational learning theory. We describe...
108
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ALT
2008
Springer
15 years 8 months ago
2008
Springer
We propose a new boosting algorithm for bipartite ranking problems. Our boosting algorithm, called SoftRankBoost, is a modification of RankBoost which maintains only smooth distri...
104
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WSDM
2010
ACM
15 years 9 months ago
2010
ACM
Queries describe the users' search intent and therefore they play an essential role in the context of ranking for information retrieval and Web search. However, most of exist...
WSDM
2010
ACM
15 years 9 months ago
2010
ACM