A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
The problem of closed frequent itemset discovery is a fundamental problem of data mining, having applications in numerous domains. It is thus very important to have efficient par...
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Mining frequent patterns on streaming data is a new challenging problem for the data mining community since data arrives sequentially in the form of continuous rapid streams. In t...