The large amount of data generated every day makes necessary the re-implementation of
new methods capable of handle with massive data efficiently. This is the case of Association …

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 …

This paper presents a decision support system 'Domain Aware Text & Association Mining
(DATAM)'which has been developed to improve after-sales service and repairs for the …

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 …

Data mining techniques managing imprecision are very useful to obtain meaningful and
interesting information for the user. Among some other techniques, fuzzy association rules …

In this paper we describe and discuss the main contributions of the representation by levels
approach to fuzzy data mining. Representation by levels is an alternative representation of …

In light of the enormous increase in data generated each day, machine learning
methodologies must be continuously improved and adapted to deal with ever-larger …

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 …

Nowadays, data volume, distribution, and volatility make it difficult to search global patterns
by applying traditional Data Mining techniques. In the case of data in a distributed …

Measures of interestingness play a crucial role in association rule mining. An important
methodological problem, on which several papers appeared in the literature, is to provide a …