User profiling in personalization applications through rule discovery and validation
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
A broader approach to personalization
Communications of the ACM
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
WEBKDD 2002: Web mining for usage patterns & profiles
ACM SIGKDD Explorations Newsletter
The Role of Structured Content in a Personalized News Service
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 7 - Volume 7
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Customized Internet news services based on customer profiles
ICEC '03 Proceedings of the 5th international conference on Electronic commerce
Efficient Web Log Mining for Product Development
CW '03 Proceedings of the 2003 International Conference on Cyberworlds
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 7 - Volume 7
Identifying Interesting Customers through Web Log Classification
IEEE Intelligent Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Personalization technologies: a process-oriented perspective
Communications of the ACM - The digital society
Dynamic personalization of web sites without user intervention
Communications of the ACM - Spam and the ongoing battle for the inbox
A time-based approach to effective recommender systems using implicit feedback
Expert Systems with Applications: An International Journal
Mobile commerce: its market analyses
International Journal of Mobile Communications
Assessing users' product-specific knowledge for personalization in electronic commerce
Expert Systems with Applications: An International Journal
A preference scoring technique for personalized advertisements on Internet storefronts
Mathematical and Computer Modelling: An International Journal
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Recent studies have indicated an increase in customer profiling techniques used by e-commerce businesses. E-commerce businesses are creating, maintaining and utilising customer profiles to assist in personalisation. Personalisation can help improve customers' satisfaction levels, purchasing behaviour, loyalty and subsequently improve sales. The continuously changing customer needs and preferences pose a challenge to e-commerce businesses on how to maintain and update individual customer profiles to reflect any changes in customers' needs and preferences. This research set out to investigate how a dynamic customer profile for on-line customers can be updated and maintained, taking into consideration individual web visitors' activities. The research designed and implemented a decision model that analysed on-line customers' activities during interaction sessions and determined whether to update customers' profiles or not. Evaluation results indicated that the model was able to analyse the on-line customers' activities from a log file and successfully updated the customers' profiles, based on the customer activities undertaken during the interaction session.