30 search results - page 4 / 6 » Query-level loss functions for information retrieval |
CIKM
2009
Springer
13 years 10 months ago
2009
Springer
Traditional ranking mainly focuses on one type of data source, and effective modeling still relies on a sufficiently large number of labeled or supervised examples. However, in m...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
WSDM
2010
ACM
13 years 11 months ago
2010
ACM
Ranking a set of retrieved documents according to their relevance to a given query has become a popular problem at the intersection of web search, machine learning, and informatio...
SIGIR
2002
ACM
13 years 5 months ago
2002
ACM
tion Abstract ChengXiang Zhai (Advisor: John Lafferty) Language Technologies Institute School of Computer Science Carnegie Mellon University With the dramatic increase in online in...
SIGIR
2008
ACM
13 years 6 months ago
2008
ACM
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...