A Fast Algorithm for Mining Association Rules in Web Log Data

상품간 연관 규칙의 효율적 탐색 방법에 관한 연구 : 인터넷 쇼핑몰을 중심으로

Mining association rules in web log files can be divided into two steps: 1) discovering frequent item sets in web data; 2) extracting association rules from the frequent item sets found in the previous step. This paper suggests an algorithm for finding frequent item sets efficiently The essence of the proposed algorithm is to transform transaction data files into matrix format. Our experimental results show that the suggested algorithm outperforms the Apriori algorithm, which is widely used to discover frequent item sets, in terms of scan frequency and execution time.