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» Learning to rank for information retrieval (LR4IR 2008)
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SIGIR
2004
ACM
15 years 11 months ago
Learning to cluster web search results
Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't g...
Hua-Jun Zeng, Qi-Cai He, Zheng Chen, Wei-Ying Ma, ...
CIKM
2000
Springer
15 years 10 months ago
Relevance and Reinforcement in Interactive Browsing
We consider the problem of browsing the top ranked portion of the documents returned by an information retrieval system. We describe an interactive relevance feedback agent that a...
Anton Leuski
ECIR
2009
Springer
16 years 3 months ago
Joint Ranking for Multilingual Web Search
Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s langu...
Wei Gao, Cheng Niu, Ming Zhou, Kam-Fai Wong
ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
16 years 29 days ago
Image ranking with implicit feedback from eye movements
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
David R. Hardoon, Kitsuchart Pasupa
ECIR
2008
Springer
15 years 7 months ago
Evaluating Paragraph Retrieval for
Abstract. We implemented a baseline approach to why-question answering based on paragraph retrieval. Our implementation incorporates the QAP ranking algorithm with addition of a nu...
Suzan Verberne, Lou Boves, Nelleke Oostdijk, Peter...