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» Learning to rank on graphs
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CIVR
2008
Springer
245views Image Analysis» more  CIVR 2008»
15 years 8 months ago
Probabilistic optimized ranking for multimedia semantic concept detection via RVM
We present a probabilistic ranking-driven classifier for the detection of video semantic concept, such as airplane, building, etc. Most existing concept detection systems utilize ...
Yantao Zheng, Shi-Yong Neo, Tat-Seng Chua, Qi Tian
ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
16 years 1 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
SIGIR
2009
ACM
16 years 28 days 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
ML
2010
ACM
142views Machine Learning» more  ML 2010»
15 years 4 months ago
Graph regularization methods for Web spam detection
We present an algorithm, witch, that learns to detect spam hosts or pages on the Web. Unlike most other approaches, it simultaneously exploits the structure of the Web graph as wel...
Jacob Abernethy, Olivier Chapelle, Carlos Castillo
ICDE
2009
IEEE
251views Database» more  ICDE 2009»
16 years 8 months ago
Contextual Ranking of Keywords Using Click Data
The problem of automatically extracting the most interesting and relevant keyword phrases in a document has been studied extensively as it is crucial for a number of applications. ...
Utku Irmak, Vadim von Brzeski, Reiner Kraft