From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
WebMate: a personal agent for browsing and searching
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Selecting Examples for Partial Memory Learning
Machine Learning
A vector space model for automatic indexing
Communications of the ACM
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Dynamic user profiles based on boolean formulas
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Using Ontology to Enhance Collaborative Recommendation Based on Community
WAIM '08 Proceedings of the 2008 The Ninth International Conference on Web-Age Information Management
Modeling wine preferences by data mining from physicochemical properties
Decision Support Systems
Use of Granularity and Coverage in a User Profile Model to Personalise Visual Content Retrieval
CENTRIC '09 Proceedings of the 2009 Second International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies, and Services
Contextual search using ontology-based user profiles
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
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In view of the needs of e-commerce website for recommendation system, user interest is divided into long-term interest and short-term interest, furthermore, based on long-term interest and short-term interest, a way to describe user-s preferences is proposed. Utilising the data from the web server database, using unsupervised learning, user's registration information can be fully mined to abstract user's long-term interest. Based on vector mapping, both the records data and content data on the server log is analysed to abstract user's short-term interest. Moreover, the rough profile presenting user's preferences can be modified by dealing with user's feedback, making updating user's preferences profile possible. Case analysis illustrates that to a certain extent this method is reasonable and feasible.