Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Abstract. We investigate the problem of finding frequent patterns in a continuous stream of transactions. It is recognized that the approximate solutions are usually sufficient and...
Research in the field of knowledge discovery from temporal data recently focused on a new type of data: interval sequences. In contrast to event sequences interval sequences contai...
This work discusses the problem of generating association rules from a set of transactions in a relational database, taking performance and accuracy of found results as the essent...
The mining of frequent patterns in databases has been studied for several years. However, the real-world data tends to be dirty and frequent pattern mining which extracts patterns...