Quality of Extracted Sequential Rules by Session Identification Using STT and Cookies

摘要

The data source of web usage mining is a web server access log file. This paper is focus on the user session identification that is the important step of data pre-processing. There are two useful methods to identification user and session: Session Time Thresholds (STT) and cookies identification. We identified user/session with cookies and STT methods and create different data pre-processing files. We will compare the user/session identification according to following levels of data pre-processing. By comparing these methods, we focused on the quality of extracted sequential rules. Sequence rules are an important output of the web usage mining process. Generated sequential rules from pre-processed files are classified into one of the following groups: useful, trivial, inexplicable. The aim of our paper is to compare the user/session identification using cookies with the identification of user/session using the STT. This comparison was performed with respect to the quality of the sequential rules generated, i.e., a comparison was made in terms of generation useful, trivial and inexplicable rules.