On a data warehouse, either manual analyses supported by appropriate visualization tools
or (semi-) automatic data mining may be performed, eg clustering, classification and …

In recent years, the progress in hardware technology has made it possible for organizations
to store and record large streams of transactional data. This results in databases which grow …

The discovery of frequent sequences in temporal databases is an important data mining
problem. Most current work assumes that the database is static, and a database update …

Most previous work on periodicy detection has focused on mining synchronous periodic
patterns and does not recognize misaligned presence of a pattern due to the intervention of …

Understanding and adapting to changes of customer behavior is an important aspect for a
internet-based company to survive in a continuously changing environment. The aim of this …

Mining association rules with multiple minimum supports is an important generalization of
the association-rule-mining problem, which was recently proposed by Liu et al. Instead of …

In this paper, we consider the problem of the incremental mining of sequential patterns when
new transactions or new customers are added to an original database. We present a new …

Efficient discover of association rules in large databases is a we 1 studied problem and
several ap-1y proaches have been proposed. However, it is non trivial to maintain the …

In many e-commerce applications, ranging from dynamic Web content presentation, to
personalized ad targeting, to individual recommendations to the customers, it is important to …

Data mining (DM) is the extraction of regularities from raw data, which are further
transformed within the wider process of knowledge discovery in databases (KDD) into non …