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SUGGETIONS TO IMPROVE THE EFFICIENCY OF ASSOCIATION RULESTECHNIQUES IN DATA MINING | ||
| AL-TAQANI | ||
| Article 1, Volume 23, Issue 4, 2010, Pages 32-41 | ||
| Authors | ||
| Hillal Hadi Salih; Soukaena Hassan Hash; Shaimaa Akram Hassan | ||
| Abstract | ||
| Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships that can be hidden among vast amount of data. From these businesses and organizations can make valid predictions about future trends in all areas of business. Association rule mining is a typical approach used in data mining domain for uncovering interesting trends, patterns and rules in large datasets This research concentrates on one particular aspect to improve the efficiency of the association rules technique in data mining by the following: 1. With databases have large set of items, it suggested to find the frequent itemsets by using depth search. In detail that done by finding the largest frequent itemset and then finding all the sub frequent itemsets from it. This proposal aim will speed up the process of finding frequent itemsets. 2. Classify the frequent itemsets to three classes closed frequent, maximal frequent and normal frequent. This proposal classification is important in the analysis process to support and strength the prediction with association rules. | ||
| Keywords | ||
| Association Rules; frequent itemsets; closed frequent itemsets and maximal frequent itemsets | ||
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