We present a generalization of frequent itemsets allowing the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifie...
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
Background: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to rela...
Bartek Wilczynski, Torgeir R. Hvidsten, Andriy Kry...
Abstract. In Minimum Message Length (MML) clustering (unsupervised classification, mixture modelling) the aim is to infer a set of classes that best explains the observed data ite...
This paper introduces a fast data dissemination method for structured peer-to-peer networks. The work is motivated on one side by the increase in non-volatile memory available on ...
Mihai Lupu, Jianzhong Li, Beng Chin Ooi, Shengfei ...