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CVPR
2007
IEEE
15 years 5 months ago
Diverse Active Ranking for Multimedia Search
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...
ERCIMDL
1999
Springer
154views Education» more  ERCIMDL 1999»
15 years 6 months ago
Effectiveness of Keyword-Based Display and Selection of Retrieval Results for Interactive Searches
Abstract. We present an approach to increasing the effectiveness of rankedoutput retrieval systems that relies on graphical display and user manipulation of “views” of retrieva...
Ezio Berenci, Claudio Carpineto, Vittorio Giannini...
CIKM
2010
Springer
15 years 10 days ago
Learning to rank relevant and novel documents through user feedback
We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Abhimanyu Lad, Yiming Yang
135
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ICML
2008
IEEE
16 years 2 months ago
Query-level stability and generalization in learning to rank
This paper is concerned with the generalization ability of learning to rank algorithms for information retrieval (IR). We point out that the key for addressing the learning proble...
Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang...
WWW
2008
ACM
16 years 2 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...