This paper focuses on the discovery of surprising, unexpected patterns, based on a data mining method that consists of detecting instances of Simpson's paradox. By its very n...
In this paper, we employ a novel approach to metarule-guided, multi-dimensional association rule mining which explores a data cube structure. We propose algorithms for metarule-gu...
We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
Time series analysis is a wide area of knowledge that studies processes in their evolution. The classical research in the area tends to find global laws underlying the behaviour o...
Abstract. This paper presents a rough set model for constraint-based multidimensional association rule mining. It first overviews the progress in constraintbased multi-dimensional ...