Mining Web Access Sequence with Improved Apriori Algorithm

Abstract

Apriori algorithm is a classic mining algorithm which can mining association rules and sequential patterns. However, when the Apriori algorithm is applied to contiguous sequential pattern mining, it is inefficient. In web log mining, the contiguous sequential pattern can better represent the semantic information of the user's access to the site due to the continuity of the user's visit to the site page. Contiguous sequential pattern can be used not only to predict the user's next access request, but also to improve the site topology structure and set the advertising page. The Apriori algorithm is used to generate a large number of candidates when mining contiguous sequence patterns, and to scan the transaction database frequently. In this paper, we present an improved algorithm that we called AC-Apriori algorithm based on the Apriori algorithm. The AC-Apriori algorithm reduces the times scanning the transaction database while preserving the full mining effect, which reduces the runtime and improves the mining efficiency compared with the Apriori algorithm.