In traditional classification setting, training data are represented as a single table, where each row corresponds to an example and each column to a predictor variable or the targ...
In this paper we describe I-Subdue, an extension to the Subdue graph-based data mining system. I-Subdue operates over sequentially received relational data to incrementally discov...
Jeffrey Coble, Diane J. Cook, Lawrence B. Holder, ...
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
—We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and ac...
In an effort to support the development of context-aware applications that use archived sensor data, we introduce the concept of the Context Cube based on techniques of data wareho...
Lonnie D. Harvel, Ling Liu, Gregory D. Abowd, Yu-X...