We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its maximal frequency ove...
Mining frequent patterns in transaction databases has been studied extensively in data mining research. However, most of the existing frequent pattern mining algorithms do not con...
This paper describes a theoretical approach on data mining, information classifying and a global overview of our OntoExtractor application, concerning the analysis of incoming data...
Zhan Cui, Ernesto Damiani, Marcello Leida, Marco V...
: Nonnegative matrix approximation (NNMA) is a popular matrix decomposition technique that has proven to be useful across a diverse variety of fields with applications ranging from...
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...