Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Increased availability of large repositories of chemical compounds has created new challenges and opportunities for the application of data-mining and indexing techniques to probl...
Monitoring predefined patterns in streaming time series is useful to applications such as trend-related analysis, sensor networks and video surveillance. Most current studies on s...
Yueguo Chen, Mario A. Nascimento, Beng Chin Ooi, A...
ions in Process Mining: A Taxonomy of Patterns R.P. Jagadeesh Chandra Bose1,2 and Wil M.P. van der Aalst1 1 Department of Mathematics and Computer Science, University of Technology...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
In this paper, we propose the "Democratic Classifier", a simple, democracy-inspired patternbased classification algorithm that uses very short patterns for classificatio...