Information filtering based on user behavior analysis and best match text retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Experience with personalization of Yahoo!
Communications of the ACM
Web usage mining for Web site evaluation
Communications of the ACM
A broader approach to personalization
Communications of the ACM
Automatic personalization based on Web usage mining
Communications of the ACM
Communications of the ACM
Adaptive interfaces for ubiquitous web access
Communications of the ACM - The Adaptive Web
Capturing the Semantics of Weg Log Data by Navigation Matrices
Proceedings of the IFIP TC2/WG2.6 Ninth Working Conference on Database Semantics: Semantic Issues in E-Commerce Systems
Adoption of Internet-Based Product Customization and Pricing Strategies
Journal of Management Information Systems
Client-side dynamic metadata in web 2.0
SIGDOC '07 Proceedings of the 25th annual ACM international conference on Design of communication
Ontology-Based Fraud Detection
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
The Influence of Cognitive and Personality Characteristics on User Navigation: An Empirical Study
UAHCI '09 Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services
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Many online firms are investing money in various means and methods to track online customers' navigation patterns and analyze their characteristics and their web behaviours. With better understanding of the navigation patterns, the firms can provide breakthrough customer service. Currently, there are numerous frameworks ready to help the firms realise their dream to understand their customers. However, these frameworks are limited to server-sided tracking, and the firms lose their customers' footprints once the customers leave their web sites. Therefore, this paper proposes a framework of user remote tracker, and this tracking method can be used to discover much value of customer information. We implemented this tracker, and used it to record the Internet activities from web users in a controlled lab experiment setting. We performed preliminary data analysis to draw a linkage between web customers' characteristics (such as personality traits) and their browsing behaviors.