M. Amparo Vila

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Fuzzy numbers, and more generally linguistic values, are approximate assessments, given by experts and accepted by decision-makers when obtaining more accurate values is impossible or unnecessary. To simplify the task of representing and handling fuzzy numbers, several authors have introduced real indices in order to capture the information contained in a(More)
The theory of fuzzy sets has been recognized as a suitable tool to model several kinds of patterns that can hold in data. In this paper, we are concerned with the development of a general model to discover association rules among items in a (crisp) set of fuzzy transactions. This general model can be particularized in several ways; each particular instance(More)
This paper shows the necessary elements for the effective implementation of the generalized fuzzy relational database model. From the model described in Medina et al. (1994) some criteria for representation and handling of imprecise information are introduced, the most important aspect being the simplicity of the implementation. The paper shows a series of(More)
Association rules are considered to be the best studied models for data mining. In this article, we propose their use in order to extract knowledge so that normal behavior patterns may be obtained in unlawful transactions from transactional credit card databases in order to detect and prevent fraud. The proposed methodology has been applied on data about(More)
The use of OLAP technology in new knowledge fields and the merge of data from different sources have made appeared new requirements for models to support this technology. What we propose in this paper is a new multidimensional model that can manage imprecision both in the dimensions and the facts. This enables the multidimensional structure to model the(More)
It has been pointed out that the usual framework to assess association rules, based on support and confidence as measures of importance and accuracy, has several drawbacks. In particular, the presence of items with very high support can lead to obtain many misleading rules, even in the order of 95% of the discovered rules in some of our experiments. In this(More)