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WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 7 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 10 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
ICCV
2007
IEEE
14 years 4 months ago
Interactive Feedback for Video Tracking Using a Hybrid Maximum Likelihood Similarity Measure
In this article, we present an object tracking system which allows interactive user feedback to improve the accuracy of the tracking process in real-time video. In addition, we des...
Ard Oerlemans, Bart Thomee
ICALT
2007
IEEE
14 years 4 months ago
Towards Advanced Learner Modeling: Discussions on Quasi Real-time Adaptation with Physiological Data
In this paper, we discuss the use of physiological data for quasi real-time adaptation in ITS. We present preliminary results where we analyze learners’ reactions while using a ...
Emmanuel G. Blanchard, Pierre Chalfoun, Claude Fra...
ICIP
2008
IEEE
15 years 16 hour ago
Long term learning for image retrieval over networks
In this paper, we present a long term learning system for content based image retrieval over a network. Relevant feedback is used among different sessions to learn both the simila...
David Picard, Arnaud Revel, Matthieu Cord