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
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Determining web users' personality traits plays a vital role in understanding user navigation patterns & behaviours on the web. This information can then be used by various online firms to provide various personalized services to online customers. There are already numerous approaches towards analyzing user behavioural patterns. The client side tracking, server---side tracking, user remote tracker etc. are some of these. However all of them have certain inherent drawbacks which make them inappropriate for multi-user environments. We propose a new integrated approach and thereby develop a unique conceptual model which would prove to be extremely advantageous even in multi-user environments. We use user clicks to analyze the user behaviour along with the content on the various websites that the user visits. We also use a personality questionnaire which would help to further enhance our results and give a better understanding of the user's personality traits.