Electronic Commerce Customer Relationship Management: A Research Agenda
Information Technology and Management
A semantic-expansion approach to personalized knowledge recommendation
Decision Support Systems
Interest-determining web browser
ICDM'10 Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects
Information Systems Frontiers
Expert Systems with Applications: An International Journal
User interests modeling based on multi-source personal information fusion and semantic reasoning
AMT'11 Proceedings of the 7th international conference on Active media technology
BI'11 Proceedings of the 2011 international conference on Brain informatics
Top-N news recommendations in digital newspapers
Knowledge-Based Systems
A web personalized service based on dual GAs
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Personalized news recommendation: a review and an experimental investigation
Journal of Computer Science and Technology - Special issue on Community Analysis and Information Recommendation
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Discovering user interests is a very important task for providing personalized services in electronic commerce. A popular approach is to develop customer profiles from their browsing behavior. In this paper, we present an approach that analyzes the browsing content and time to determine user interests. An empirical study using actual news provided by the China Times shows that the proposed system outperforms the traditional headline news compiled by the news editor in both objective performance indices and customer satisfaction.