Enterprise based approach to Mining Frequent Utility Itemsets from Transactional Database

Data mining can be used extensively in the enterprise based applications with business intelligence characteristics to provide a deeper kind of analysis while meeting strict requirements for administration management and security. Business intelligence is information about a company's past performance that is used to help predict the company's future performance. ARM is a well-known technique in the data mining field, is used to identify frequently occurring patterns of item sets. Although, frequency of occurrence may reflects the statistical correlation between items, and it does not reflect the semantic significance of the items because the user's interest may be related to other factors, such as cost and profit. Utility based itemset mining approach is used to overcome this limitation. This approach identifies itemsets with high utility like high profits. A specialized form of high utility itemset mining is utility-frequent itemset mining which is for considering the business yield and demand or rate of occurrence of the items while mining a retail business transaction database. Such a data mining process will help in mining different types of itemsets of varying business utility and demand such as HUHF, HULF,LUHF and LULF itemsets. Which would significantly helps in inventory control and sales promotion. These itemsets are generated using FUM and FUFM of algorithms which also capable of identifying the active customers of each such type of itemset mined and ranking them based on their total or lifetime business value which would be extremely helpful in improving CRM processes.