Abstract— As the datasets used to fuel modern scientific discovery grow increasingly large, they become increasingly difficult to manage using conventional software. Parallel d...
Sarah Loebman, Dylan Nunley, YongChul Kwon, Bill H...
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
: Data mining is the process of posing queries and extracting patterns, often previously unknown from large quantities of data using pattern matching or other reasoning techniques....
The publish-subscribe paradigm is an effective approach for data publishers to asynchronously disseminate relevant data to a large number of data subscribers. A lot of recent res...