AdROSA-Adaptive personalization of web advertising
Information Sciences: an International Journal
Integrating recommendation models for improved web page prediction accuracy
ACSC '08 Proceedings of the thirty-first Australasian conference on Computer science - Volume 74
Web-Based Recommender Systems and User Needs --the Comprehensive View
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
A Combined Method for Extracting Rules with Improved Quality
Proceedings of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding
An integrated model for next page access prediction
International Journal of Knowledge and Web Intelligence
Blogger-Centric Contextual Advertising
Expert Systems with Applications: An International Journal
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Because of the intelligent computing specialty of the World Wide Web, extensive customized marketing can be executed at much lower cost and has become an emerging research issue. Therefore, the first purpose of this paper is to purpose a system framework to serve as a foundation for developing a customized marketing system on the Web according to the discussions on data sources, data categories, and inference foundations.Most previous studies used induction-learning techniques to perform individual-based inference for customized marketing. However, it not only costs more to learn the personal preferences, but also some difficulties occur from using induction-learning techniques. The second purpose of this paper is to solve these problems. A group-based approach that integrates clustering and association rules is proposed. We conducted a field study to collect data to demonstrate the proposed group-based inference approach and evaluate its performance. The results reveal that this integrated approach can learn both more detailed and precise rules.