Overview of Itemset Utility Mining and its Applications

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Overview of Itemset Utility Mining and its Applications

An emerging topic in the field of data mining is Utility Mining. The main objective of Utility Mining is to identify the itemsets with highest utilities, by considering profit, quantity, cost or other user preferences. Mining High Utility itemsets from a transaction database is to find itemsets that have utility above a user-specified threshold. Itemset Utility Mining is an extension of Frequen...

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High Utility Itemset Mining

Data Mining can be defined as an activity that extracts some new nontrivial information contained in large databases. Traditional data mining techniques have focused largely on detecting the statistical correlations between the items that are more frequent in the transaction databases. Also termed as frequent itemset mining , these techniques were based on the rationale that itemsets which appe...

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A New Algorithm for High Average-utility Itemset Mining

High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its utility measurement and utility values tend to become higher for itemsets containing more items...

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Actionable Combined High Utility Itemset Mining

The itemsets discovered by traditional High Utility Itemsets Mining (HUIM) methods are more useful than frequent itemset mining outcomes; however, they are usually disordered and not actionable, and sometime accidental, because the utility is the only judgement and no relations among itemsets are considered. In this paper, we introduce the concept of combined mining to select combined itemsets ...

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Study on High Utility Itemset Mining

Data mining is the process of mining new non trivial and potentially valuable information from large data basis. Data mining has been used in the analysis of customer transaction in retail research where it is termed as market basket analysis. Earlier data mining methods concentrated more on the correlation between the items that occurs more frequent in the transaction. In frequent itemset mini...

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ژورنال

عنوان ژورنال: International Journal of Computer Applications

سال: 2010

ISSN: 0975-8887

DOI: 10.5120/956-1333