354 search results - page 5 / 71 » Top-k learning to rank: labeling, ranking and evaluation |
160
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WWW
2009
ACM
16 years 6 months ago
2009
ACM
We consider the problem of identifying the consensus ranking for the results of a query, given preferences among those results from a set of individual users. Once consensus ranki...
167
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ICML
2010
IEEE
15 years 7 months ago
2010
IEEE
This paper introduces two new methods for label ranking based on a probabilistic model of ranking data, called the Plackett-Luce model. The idea of the first method is to use the ...
203
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SIGIR
2011
ACM
14 years 9 months ago
2011
ACM
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
171
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WSDM
2010
ACM
16 years 3 months ago
2010
ACM
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
174
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ICML
2009
IEEE
16 years 26 days ago
2009
IEEE
The label ranking problem consists of learning a model that maps instances to total orders over a finite set of predefined labels. This paper introduces new methods for label ra...