Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs

Authors:
Zhixiang Chen;Ada Wai-Chee Fu;Frank Chi-Hung Tong
Affiliations:
-;-;-
Venue:
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Year:
2002

Citing 10
Cited 1

Characterizing browsing strategies in the World-Wide Web

Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
Silk from a sow's ear: extracting usable structures from the Web

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
In search of reliable usage data on the WWW

Selected papers from the sixth international conference on World Wide Web
Adaptive Web sites: automatically synthesizing Web pages

AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Discovering Internet marketing intelligence through online analytical web usage mining

ACM SIGMOD Record
Efficient Data Mining for Path Traversal Patterns

IEEE Transactions on Knowledge and Data Engineering
WUM - A Tool for WWW Ulitization Analysis

WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
Improving the Effectiveness of a Web Site with Web Usage Mining

WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Analysis of navigation behaviour in web sites integrating multiple information systems

The VLDB Journal — The International Journal on Very Large Data Bases
Discovering Web Access Patterns and Trends by Applying OLAP and Data Mining Technology on Web Logs

ADL '98 Proceedings of the Advances in Digital Libraries Conference

Fast construction of generalized suffix trees over a very large alphabet

COCOON'03 Proceedings of the 9th annual international conference on Computing and combinatorics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Although efficient identification of user access sessions from very large web logs is an unavoidable data preparation task for the success of higher level web log mining, little attention has been paid to algorithmic study of this problem. In this paper we consider two types of user access sessions, interval sessions and gap sessions. We design two efficient algorithms for finding respectively those two types of sessions with the help of new data structures. We present both theoretical and empirical analysis of the algorithms and prove that both algorithms have optimal time complexity.