Association rule mining (ARM) plays a vital role in data mining. It aims at searching for interesting pattern among items in a dense data set or database and discovers association rules among the large number of itemsets. The importance of ARM is increasing with the demand of finding frequent patterns from large data sources. Researchers developed a lot of algorithms and techniques for generati...

--The utility of an itemset represents its importance, which can be measured in terms of weight, value, quantity or other information depending on the user specification. High utility itemsets mining identifies itemsets whose utility satisfies a given threshold. It allows users to quantify the usefulness or preferences of items using different values. Thus, it reflects the impact of different i...

Mining High Utility Itemsets from a transaction database is to find itemsests that have utility above a user-specified threshold. This problem is an extension of Frequent Itemset Mining, which discovers itemsets that occur frequently (i.e. with occurrence count larger than a user given value). The problem of finding High Utility Itemsets is challenging, because the anti-monotone property so use...

High-utility itemset mining is the task of discovering highutility itemsets, i.e. sets of items that yield a high profit in a customer transaction database. High-utility itemsets are useful, as they provide information about profitable sets of items bought by customers to retail store managers, which can then use this information to take strategic marketing decisions. An inherent limitation of ...

The rationale behind mining frequent itemsets is that only itemsets with high frequency are of interest to users. However, the practical usefulness of frequent itemsets is limited by the significance of the discovered itemsets. A frequent itemset only reflects the statistical correlation between items, and it does not reflect the semantic significance of the items. In this paper, we propose a u...

High utility pattern mining becomes a very important research issue in data mining by considering the non-binary frequency values of items in transactions and different profit values for each item. These profit values can be computed efficiently inorder to determine the gain of an itemset which in-turn will help in production planning of any company. This gain value is needed to prune some of t...

Online high utility itemset mining over data streams has been studied recently. However, the existing methods are not designed for producing topk patterns. Since there could be a large number of high utility patterns, finding only top-k patterns is more attractive than producing all the patterns whose utility is above a threshold. A challenge with finding top-k high utility itemsets over data s...

Association Rule Mining (ARM) is finding out the frequent itemsets or patterns among the existing items from the given database. High Utility Pattern Mining has become the recent research with respect to data mining. The proposed work is High Utility Pattern for distributed and dynamic database. The traditional method of mining frequent itemset mining embrace that the data is astride and sedent...

Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information. It can be defined as the activity that extracts information contained in very large database. That information can be used to increase the revenue or cut costs. Association Rule Mining (ARM) is finding out the frequent itemsets or patterns among the existing items from the given ...