A New Scheme for Extracting Association Rules - Moyaid Said, Aiman (2009)
Data mining is the process of exploring and analyzing large databases to extract interesting and previously unknown patterns and rules. In the age of information technology, the amount of accumulated data is tremendous. Extracting the association rule from this data is one of the important tasks in data mining. In Data mining, association rule mining is a descriptive technique which can be defined as discovering meaningful patterns (itemsets tend to take place together in the transactions) from large collections of data. Mining frequent patterns is a fundamental part of association rules mining. Most of the previous studies adopt an a priori-like candidate set generation-and-test approach to generate the association rules from the transactional database. The priori-like candidate approach can suffer from two nontrivial costs: it needs to generate a huge number of candidate sets, and it may need to repeatedly scan the database and check a large set of candidates by pattern matching.