ARAA: A Fast Advanced Reverse Apriori Algorithm for Mining Association Rules in Web Data

This paper proposed an effective algorithm for mining frequent sequence patterns from the web data by applying association rules based on Apriori, known as Advanced Reverse Apriori Algorithm (ARAA). It also shows the limitation of existing Apriori and Reverse Apriori Algorithm. Our approach is based on the reverse scans. An experimental work is performed that shows that proposed algorithm works better than the existing two algorithms. The advantages of ARAA are that it can deeply reduce the multiple scans for frequent sequence pattern generation which results in less processing overhead. A comparative study performed on all three approaches shows that our algorithm improve the mining process significantly as compared to Apriori and Reverse Apriori based mining algorithms especially for the all database. The advantages of ARAA are reduced execution time and increase throughput. Keyword Association Rule, Apriori Algorithm, Reverse Apriori, Web Usage, Frequent Sequence Patterns