Graphs are prevailingly used in many applications to model complex data structures. In this paper, we study the problem of supergraph containment search. To avoid the NP-complete s...
Background: In Eukaryotic genomes, different features including genes are not uniformly distributed. The integration of annotation information and genomic position of functional D...
Alessandro Coppe, Gian Antonio Danieli, Stefania B...
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...