Session identification based on time interval in web log mining

Authors:
Zhuang Like;Kou Zhongbao;Zhang Changshui
Affiliations:
State Key Laboratory of Intelligent Technology and Systems, Department of Automation, Tsinghua University, Beijing, P.R. China;State Key Laboratory of Intelligent Technology and Systems, Department of Automation, Tsinghua University, Beijing, P.R. China;State Key Laboratory of Intelligent Technology and Systems, Department of Automation, Tsinghua University, Beijing, P.R. China
Venue:
Intelligent information processing II
Year:
2004

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Abstract

In this paper, we calculate the time intervals of page views, and analyze the time intervals to obtain a certain threshold, which is then used to break the web logs into sessions. Based on the time intervals, frequencies for each interval are counted and frequency vectors are obtained for each IP. Some IPs with special features of frequency distributions can be deemed as single users. For these IPs, we can define threshold for each individual IP, and separate sessions at the points of long access time intervals.