Pattern mining is a fundamental technique of data mining to discover interesting correlations
in the data set. There are several variations of pattern mining, such as frequent itemset …

High utility pattern mining is an emerging data science task, which consists of discovering
patterns having a high importance in databases. The utility of a pattern can be measured in …

Discovering high utility itemsets in transaction databases is a key task for studying the
behavior of customers. It consists of finding groups of items bought together that yield a high …

High-utility itemset mining is the task of discovering high-utility itemsets, ie sets of items that
yield a high profit in a customer transaction database. High-utility itemsets are useful, as they …

High-utility itemset mining (HUIM) is an important task in the field of knowledge data
discovery. The large search space and huge number of HUIs are the consequences of …

Mining high utility itemsets are the basic task in the area of frequent itemset mining (FIM) that
has various applications in diverse domains, including market basket analysis, web mining …

Abstract High Utility Sequential Pattern mining (HUSP) algorithms aim to find all the high
utility sequences from a sequence database. Due to the large explosion of data, recently few …

Frequent closed itemsets provide a lossless and concise collection of all frequent itemsets to
reduce the runtime and memory requirement of frequent itemsets mining tasks. This study …

High utility itemset (HUI) mining is emerging as an effective pattern mining technique, which
discovers itemsets with their utility more than user defined utility threshold. Most of the HUI …

The set of closed high-utility itemsets (CHUIs) concisely represents the exact utility of all
itemsets. Yet, it can be several orders of magnitude smaller than the set of all high-utility …