GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Maintaining knowledge about temporal intervals
Communications of the ACM
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Accelerating XPath location steps
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Integrating Web Usage and Content Mining for More Effective Personalization
EC-WEB '00 Proceedings of the First International Conference on Electronic Commerce and Web Technologies
A Survey of Context-Aware Mobile Computing Research
A Survey of Context-Aware Mobile Computing Research
Design and implement of customer information retrieval system based on semantic web
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
User preference through learning user profile for ubiquitous recommendation systems
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Automatic classification for grouping designs in fashion design recommendation agent system
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Optimal associative neighbor mining using attributes for ubiquitous recommendation systems
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
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As Ubiquitous commerce is coming, personalization service is getting interested. And also the recommendation method that offers useful information to the customers becomes more important. However, the previous methods depend on specific method and are restricted to the E-commerce. For applying these recommendation methods into U-commerce, we propose a modeling technique of context information related to personal activation in commercial transaction and show incremental preference analysis method, using preference tree which is closely connected to recommendation method in each step. And also, we use an XML indexing technique to efficiently extract the recommendation information from a preference tree.