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Classical attribute-value descriptions induce a multi-dimensional geometric space. One way for computing the distance between descriptions in such a space consists in evaluating an Euclidean distance between tuples of coordinates. This is the ground on which a large part of the Machine Learning literature has built its methods and techniques. However, the complexity of some domains require the use...
Clustering is an active research topic in data mining and different methods have been proposed in the literature. Most of these methods are based on the use of a distance measure defined either on numerical attributes or on categorical attributes. However, in fields such as road traffic and medicine, datasets are composed of numerical and categorical attributes. Recently, there have been several proposals...
In sequential pattern mining, languages based on regular expressions (RE) were proposed to restrict frequent sequences to the ones that satisfy user-specified constraints. In these languages, REs are applied over items. We propose a much powerful language, based on regular expressions, denoted RE-SPaM, where the basic elements are constraints over the attributes of the items. Expressions in this language...
Motivated by the need for unification of the field of data mining and the growing demand for formalized representation of outcomes of research, we address the task of constructing an ontology of data mining. The proposed ontology, named OntoDM, is based on a recent proposal of a general framework for data mining, and includes definitions of basic data mining entities, such as datatype and dataset,...
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