Algorithms for clustering data
Algorithms for clustering data
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Footprints: history-rich tools for information foraging
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
The Relative Neighborhood Graph, with an Application to Minimum Spanning Trees
Journal of the ACM (JACM)
Automatic personalization based on Web usage mining
Communications of the ACM
Towards adaptive Web sites: conceptual framework and case study
Artificial Intelligence - Special issue on Intelligent internet systems
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Evaluation of Item-Based Top-N Recommendation Algorithms
Proceedings of the tenth international conference on Information and knowledge management
Modern Information Retrieval
Recommendation systems: a probabilistic analysis
Journal of Computer and System Sciences - Special issue on Internet algorithms
Personalization of Supermarket Product Recommendations
Data Mining and Knowledge Discovery
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Efficient Adaptive-Support Association Rule Mining for Recommender Systems
Data Mining and Knowledge Discovery
Mining the Web: Discovering Knowledge from HyperText Data
Mining the Web: Discovering Knowledge from HyperText Data
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A Collaborative Approach to User Modeling for Personalized Content Recommendations
ICADL 08 Proceedings of the 11th International Conference on Asian Digital Libraries: Universal and Ubiquitous Access to Information
Modeling Engagement in Educational Adaptive Hypermedia
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Resource Management Strategies for the Mobile Web
Mobile Networks and Applications
Modeling and learning user profiles for personalized content service
ICADL'07 Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers
In-depth behavior understanding and use: The behavior informatics approach
Information Sciences: an International Journal
A General Framework for Web Content Filtering
World Wide Web
Co-clustering analysis of weblogs using bipartite spectral projection approach
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
Co-clustering for weblogs in semantic space
WISE'10 Proceedings of the 11th international conference on Web information systems engineering
Transaction models for Web accessibility
World Wide Web
Collaborative user modeling for enhanced content filtering in recommender systems
Decision Support Systems
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The growing availability of information on the Web has raised a challenging problem: can a Web-based information system tailor itself to different user requirements with the ultimate goal of personalizing and improving the users' experience in accessing the contents of a website? This paper proposes a new approach to website personalization based on the exploitation of user browsing interests together with content and usage similarities among Web pages. The outcome is the delivery of page recommendations which are strictly related to the navigational purposes of visitors and their actual location within the cyberspace of the website. Our approach has been used effectively for developing a non-invasive system which allows Web users to navigate through potentially interesting pages without having a basic knowledge of the website structure.