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» A Probability Model for Combining Ranks
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SSD
2007
Springer
124views Database» more  SSD 2007»
15 years 3 months ago
Querying Objects Modeled by Arbitrary Probability Distributions
In many modern applications such as biometric identification systems, sensor networks, medical imaging, geology, and multimedia databases, the data objects are not described exact...
Christian Böhm, Peter Kunath, Alexey Pryakhin...
86
Voted
SIGIR
2009
ACM
15 years 4 months ago
Combining LVCSR and vocabulary-independent ranked utterance retrieval for robust speech search
Well tuned Large-Vocabulary Continuous Speech Recognition (LVCSR) has been shown to generally be more effective than vocabulary-independent techniques for ranked retrieval of spo...
J. Scott Olsson, Douglas W. Oard
90
Voted
NIPS
2008
14 years 11 months ago
Global Ranking Using Continuous Conditional Random Fields
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
76
Voted
ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
15 years 4 months ago
Image ranking with implicit feedback from eye movements
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
David R. Hardoon, Kitsuchart Pasupa
KDD
2002
ACM
187views Data Mining» more  KDD 2002»
15 years 10 months ago
Transforming classifier scores into accurate multiclass probability estimates
Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...
Bianca Zadrozny, Charles Elkan