K-Means clustering is widely used in information retrieval and data mining. Distributed K-Means variants have already been proposed, but none of the past algorithms scales to large...
Odysseas Papapetrou, Wolf Siberski, Fabian Leitrit...
In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is mo...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...
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...
Objective: Knowledge acquisition and maintenance in medical domains with a large application domain ontology is a difficult task. To reduce knowledge elicitation costs, semiautoma...
Software developers have long known that project success requires a robust understanding of both technical and social linkages. However, research has largely considered these inde...
Anita Sarma, Larry Maccherone, Patrick Wagstrom, J...