Contextual advertising on web pages has become very popular recently and it poses its own set of unique text mining challenges. Often advertisers wish to either target (or avoid) ...
Yi Zhang, Arun C. Surendran, John C. Platt, Mukund...
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...
We consider the problem of estimating occurrence rates of rare events for extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In pa...
Deepak Agarwal, Andrei Z. Broder, Deepayan Chakrab...