Intrusion detection systems (IDS) are commonly categorized into misuse based, anomaly
based and specification based IDS. Both misuse based IDS and anomaly based IDS are …

In this paper, we provide a brief summary of elementary research in rule learning. The two
main research directions are descriptive rule learning, with the goal of discovering …

The development of information technologies has enabled real-time monitoring and controls
over building operations. Massive amounts of building operational data are being collected …

Analyzing customer transactions to discover high-utility itemsets is a popular task, which
consists of finding the sets of items that are purchased together and yield a high profit …

The success of electronic sports (eSports), where professional gamers participate in
competitive leagues and tournaments, brings new challenges for the video game industry …

Sequential pattern mining (SPM) plays an important role in data mining, with broad
applications such as in financial markets, education, medicine, and prediction. Although …

Finding small sets of interesting patterns is an important challenge in pattern mining. In this
paper, we argue that several well-known approaches that address this challenge are based …

Mining class association rules (CARs) is an essential, but time-intensive task in Associative
Classification (AC). A number of algorithms have been proposed to speed up the mining …

The problem of mining frequent sequential patterns (FSPs) has attracted a great deal of
research attention. Although there are many efficient algorithms for mining FSPs, the mining …

Mining frequent simultaneous attribute co-variations in numerical databases is also called
frequent gradual pattern problem. Few efficient algorithms for automatically extracting such …