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...
In this paper, we present a semi-supervised learning method for web page classification, leveraging click logs to augment training data by propagating class labels to unlabeled si...
Soo-Min Kim, Patrick Pantel, Lei Duan, Scott Gaffn...