Session identification based on time intervals in Web log mining
Zhang Changshui · Journal of Tsinghua University(Science and Technology) · 2005
This paper presents a method for session identification based on an analysis of intervals of user access logs. This method separates the access logs into distinct sessions at points where the access intervals exceed some threshold. The threshold for a specific IP is defined by the statistic of its frequency vectors. Tests show that the frequency vectors of proxy IPs and single user IPs are different. For a proxy IP, the frequency vector often shows a power-law distribution, however for a single user IP, it approximates a Gauss distribution. A method based on the Gauss hypothesis was proposed for computing different thresholds for each single user IP. Compare to the traditional approach that experimentially defines a uniform threshold for all IP addresses, the method presented is more reasonable and effective.