FI-FCM Algorithm for Business Intelligence
Business Intelligence combines the large data with analytical tools to present knowledge to the decision makers. It is used to understand the trends,future directions ,capabilities and technologies in the business. It has set of methods, process and technologies that transform raw data into meaningful information. Data Mining is one of Business Intelligence techniques that are used to obtain knowledge from data. The applications of business intelligence includes E-commerce recommender system, approval of bank loan, credit/debit card fraud detection etc., In this paper we have proposed FI-FCM algorithm for Business intelligence based on frequent itemsets and Fuzzy C Means clustering to extract the intelligence from the dataset in order to make the decision making process more efficient and to improve the business intelligence. E-commerce recommender system applications is selected to experiment this algorithm to help customers to find ,recommend products they wish to purchase by producing the list of recommended products.
KeywordsBusiness Intelligence Frequent Itemset k-means Clustering Data Mining Decision Making Recommender system E-commerce
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