In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spec...
Cai-Nicolas Ziegler, Sean M. McNee, Joseph A. Kons...
This paper presents a methodology for increasing undergraduate Computer Science (CS) major enrollment at comprehensive public universities, particularly those that have first gene...
Data clustering is an important task in many disciplines. A large number of studies have attempted to improve clustering by using the side information that is often encoded as pai...
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Many users are familiar with the interesting but limited functionality of Data Detector interfaces like Microsoft's Smart Tags and Google's AutoLink. In this paper we si...