IEEE Transactions on Pattern Analysis and Machine Intelligence
Communications of the ACM
Mining e-commerce data: the good, the bad, and the ugly
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Reorganizing web sites based on user access patterns
Proceedings of the tenth international conference on Information and knowledge management
Discovery of Web Robot Sessions Based on their Navigational Patterns
Data Mining and Knowledge Discovery
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
Data Mining and Knowledge Discovery
E-Commerce User Experience
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Discovery of Interesting Usage Patterns from Web Data
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Data Mining of User Navigation Patterns
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
A Framework for Efficient and Anonymous Web Usage Mining Based on Client-Side Tracking
WEBKDD '01 Revised Papers from the Third International Workshop on Mining Web Log Data Across All Customers Touch Points
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Measuring e-Commerce effectiveness: a conceptual model
SAICSIT '03 Proceedings of the 2003 annual research conference of the South African institute of computer scientists and information technologists on Enablement through technology
Lessons and Challenges from Mining Retail E-Commerce Data
Machine Learning
The design and evaluation of accessibility on web navigation
Decision Support Systems
An empirical study of web site navigation structures' impacts on web site usability
Decision Support Systems
Mining web navigations for intelligence
Decision Support Systems - Special issue: Intelligence and security informatics
A pattern restore method for restoring missing patterns in server side clickstream data
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
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This paper describes a novel web usage mining approach to discover patterns in the navigation of websites known as Unexpected Navigation Behaviours (UNBs). The approach provides a web designer with a means of identifying and classifying patterns of browsing and, by reviewing these patterns, the designer can then choose to modify the design of their site or redesign it completely. UNB mining is based on the Consecutive Common Subsequence (CCS), a special instance of Common Subsequence (CS), which is used to define a set of expected routes. The predefined expected routes are then treated as rules and stored in a rule base. By using the predefined route and the UNB mining algorithm, interesting navigation behaviours can be discovered. This paper will introduce the format of the expected route and describe the UNB algorithms. It will also describe a tool that a website designer can use to define the expected route more efficiently, which can help the website designer to make decision about where and how the design of website can be improved. The paper concludes with a series of experiments designed to evaluate how well the UNB mining algorithms work and demonstrate how UNB mining can be useful for improving website design.