High-utility itemset mining (HUIM) is an important research topic in data mining field and extensive algorithms have been proposed. However, existing methods for HUIM present too many high-utility itemsets (HUIs), which reduces not only efficiency but also effectiveness of mining since users have to sift through a large number of HUIs to find useful ones. Recently a new representation, closed +...

Utility of an itemset is considered as the value of this itemset, and utility mining aims at identifying the itemsets with high utilities. The temporal high utility itemsets are the itemsets whose support is larger than a pre-specified threshold in current time window of the data stream. Discovery of temporal high utility itemsets is an important process for mining interesting patterns like ass...

Utility mining is the study of itemset mining from the consideration of utilities. It is the utility-based itemset mining approach to find itemsets conforming to user preferences. Modern research in mining high-utility itemsets (HUI) from the databases faces two major challenges: exponential search space and database-dependent minimum utility threshold. The search space is extremely vast when t...

In the ever-growing world, concepts of High-utility Itemset Mining (HUIM) as well Frequent (FIM) are fundamental works in knowledge discovery. Several algorithms have been designed successfully. However, these only used one factor to estimate an itemset. past, skyline pattern mining by considering both aspects frequency and utility has extensively discussed. most cases, however, people tend foc...

Although support has been used as a fundamental measure to determine the statistical importance of an itemset, it can’t express other richer information such as quantity sold, unit profit, or other numerical attributes. To overcome the shortcoming, utility is used to measure the semantic importance and several algorithms for utility mining have been proposed. However, existing algorithms for ut...

Utility mining emerged to overcome the limitations of frequent itemset mining by considering the utility of an item. Utility of an item is based on user’s interest or preference. Recently, temporal data mining has become a core technical data processing technique to deal with changing data. On-shelf utility mining considers on-shelf time period of item and gets the accurate utility values of it...