In this work we introduce a new approach to linguistic summarization of time series based
on the use of a fuzzy hierarchical partition of the time dimension and the evaluation of …

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 …

Association rules have been widely used in many application areas to extract new and
useful information expressed in a comprehensive way for decision makers from raw data …

In this paper, we propose a methodology for providing linguistic answers to queries
involving the comparison of time series obtained from data cubes with time dimension. Time …

In this paper a methodology is proposed for providing a linguistic summary of the
comparison of time series. This series are obtained as a result of queries which the user …

The health care environment still needs knowledge based discovery for handling wealth of
data. Extraction of the potential causes of the diseases is the most important factor for …

The paper presents a new approach to fuzzy classification in the case of missing data.
Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough …

In this work, a Multi-Objective Evolutionary Algorithm (MOEA) is developed to identify
Functional Dependencies (FDEPs) in Complex Technical Infrastructures (CTIs) from alarm …

In association rule mining, evaluating an association rule needs to repeatedly scan
database to compare the whole database with the antecedent, consequent of a rule and the …

Healthcare data need an accurate diagnosis of diseases with the low computation time.
Fuzzy association rule mining converts quantitative attributes to fuzzy attributes which …