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» Learning and Inference with Constraints
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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 10 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
KDD
2007
ACM
186views Data Mining» more  KDD 2007»
14 years 10 months ago
An Ad Omnia Approach to Defining and Achieving Private Data Analysis
We briefly survey several privacy compromises in published datasets, some historical and some on paper. An inspection of these suggests that the problem lies with the nature of the...
Cynthia Dwork
KDD
2006
ACM
127views Data Mining» more  KDD 2006»
14 years 10 months ago
Recommendation method for extending subscription periods
Online stores providing subscription services need to extend user subscription periods as long as possible to increase their profits. Conventional recommendation methods recommend...
Tomoharu Iwata, Kazumi Saito, Takeshi Yamada
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 10 months ago
Web usage mining based on probabilistic latent semantic analysis
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
SDM
2009
SIAM
394views Data Mining» more  SDM 2009»
14 years 7 months ago
Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
Many real-world applications call for learning predictive relationships from multi-modal data. In particular, in multi-media and web applications, given a dataset of images and th...
Oksana Yakhnenko, Vasant Honavar