812 search results - page 27 / 163 » Preference-based learning to rank |
LREC
2010
13 years 11 months ago
2010
Learning texts contain much implicit knowledge which is ideally presented to the learner in a structured manner - a typical example being definitions of terms in the text, which w...
SIGIR
2008
ACM
13 years 9 months ago
2008
ACM
Some applications have to present their results in the form of ranked lists. This is the case of many information retrieval applications, in which documents must be sorted accordi...
CIKM
2010
Springer
13 years 8 months ago
2010
Springer
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
IR
2010
13 years 8 months ago
2010
LETOR is a benchmark collection for the research on learning to rank for information retrieval, released by Microsoft Research Asia. In this paper, we describe the details of the L...
ICCV
2009
IEEE
13 years 7 months ago
2009
IEEE
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...