A novel approach to mining access patterns
Xiuming Yu, Meijing Li, Hyeongsoo Kim, Dong Gyu Lee, Jeong Seok Park, Keun Ho Ryu · 2011
Web log mining is an important area of Web Usage Mining (WUM) for discovering useful information from web log files produced by web servers. According to the mining task, user access patterns can be extracted and the result can be applied to improve websites, business intelligence systems and other areas. In this paper, we propose a novel approach for exacting user access patterns by achieving a large event set and improving the BI-Directional Extension closure checking method (BIDE). The process of getting a large event set can filter out the more frequent events and discard the infrequent events to reduce the number of data. Compared with other methods, the BIDE method with the constraint of gap can achieve a more efficient mining process and generate more accurate results. In our experiment, the effect of the mining task is discussed and the applications of this approach are presented.