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 …

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

The advance in information technology has enabled the real-time monitoring and controls
over building operations. Massive amounts of building operational data are being collected …

Mining gradual rules of the form−“the more A, the more B”− is more and more grasping the
interest of the data mining community. Several approaches have been recently proposed …

Mining association rules is a well known framework for extracting useful knowledge from
databases. Despite their proven applicability there exist other approaches that also search …

Fuzzy sequential pattern mining is a relevant approach when dealing with temporally
annotated numerical data since it allows discovering frequent sequences embedded in the …

Gradual Patterns allow to express frequent patterns like “the older an employee, the higher
his/her income”. After having been extensively used for fuzzy command (eg,“the closer the …

We propose a novel framework and an algorithm for mining gradual dependencies between
attributes in a data set. Our approach is based on the use of fuzzy rank correlation for …

Gradual itemsets of the form “the more/less A, the more/less B” extract knowledge in the form
of correlations between attributes. The methods for extracting such itemsets can generate …