We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
We consider the problem of finding duplicates in data streams. Duplicate detection in data streams is utilized in various applications including fraud detection. We develop a solu...
E-commerce stretches interactions over space and time, and thus requires more trust than traditional shopping. Current approaches to building trust in e-commerce focus on cognitiv...
d abstract) John Kececioglu and Dean Starrett Department of Computer Science The University of Arizona Tucson AZ 85721, USA A basic computational problem that arises in both the...
As the accuracy of conventional classifiers, based only on a static partitioning of feature space, appears to be approaching a limit, it may be useful to consider alternative appro...