Machine learning, data mining, and several related research areas are concerned with
methods for the automated induction of models and the extraction of interesting patterns …

Mining gradual rules plays a crucial role in many real world applications where huge
volumes of complex numerical data must be handled, eg, biological databases, survey …

The development of information technologies has enabled real-time monitoring and controls
over building operations. Massive amounts of building operational data are being collected …

Looking for associations in data is one of the data mining tasks that has aroused more
interest in the literature. In this area, incorporating concepts of fuzzy set theory is useful in …

The high computational impact when mining fuzzy association rules grows significantly
when managing very large data sets, triggering in many cases a memory overflow error and …

Gradual dependencies of the form the more A, the more B offer valuable information that
linguistically express relationships between variations of the attributes. Several …

Gradual patterns allow for retrieval of the correlations between attributes through rules such
as" the more exercise, the less stress". However, it is possible that a temporal lag may exist …

This paper clarifies the relation between case-based prediction and analogical transfer.
Case-based prediction consists in predicting the outcome associated with a new case …

Even if they have proven to be relevant on traditional transactional databases, data mining
tools are still inefficient on some kinds of databases. In particular, databases containing …

Mining frequent simultaneous attribute co-variations in numerical databases is also called
frequent gradual pattern problem. Few efficient algorithms for automatically extracting such …