3395 search results - page 303 / 679 » Learning to efficiently rank |
185
Voted
SAC
2010
ACM
15 years 11 months ago
2010
ACM
We consider the problem of anomaly detection in multiple co-evolving data streams. In this paper, we introduce FRAHST (Fast Rank-Adaptive row-Householder Subspace Tracking). It au...
167
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ACL
2007
15 years 8 months ago
2007
Even in a massive corpus such as the Web, a substantial fraction of extractions appear infrequently. This paper shows how to assess the correctness of sparse extractions by utiliz...
164
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TREC
2004
15 years 8 months ago
2004
While participating in the HARD track our first question was, what an IR-application should look like that takes into account preference meta-data from the user, without the need ...
187
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CORR
2006
Springer
15 years 6 months ago
2006
Springer
Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well kn...
132
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SIGIR
2008
ACM
15 years 6 months ago
2008
ACM
There has been recent interest in collecting user or assessor preferences, rather than absolute judgments of relevance, for the evaluation or learning of ranking algorithms. Since...