A massively parallel architecture for a self-organizing neural pattern recognition machine
Computer Vision, Graphics, and Image Processing
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Adaptive resonance associative map
Neural Networks
Using agents to personalize the Web
Proceedings of the 2nd international conference on Intelligent user interfaces
Siteseer: personalized navigation for the Web
Communications of the ACM
PowerBookmarks: a system for personalizable Web information organization, sharing, and management
WWW '99 Proceedings of the eighth international conference on World Wide Web
Experience with personalization of Yahoo!
Communications of the ACM
Communications of the ACM
FOCI: flexible organizer for competitive intelligence
Proceedings of the tenth international conference on Information and knowledge management
Principal Direction Divisive Partitioning
Data Mining and Knowledge Discovery
Adding Personality to Information Clustering
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Cascade ARTMAP: integrating neural computation and symbolic knowledge processing
IEEE Transactions on Neural Networks
Predictive neural networks for gene expression data analysis
Neural Networks
Intelligence Through Interaction: Towards a Unified Theory for Learning
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Towards a graph-based user profile modeling for a session-based personalized search
Knowledge and Information Systems
Agent-augmented co-space: toward merging of real world and cyberspace
ATC'10 Proceedings of the 7th international conference on Autonomic and trusted computing
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The Flexible Organizer for Competitive Intelligence (FOCI) is a personalised web intelligence system that provides an integrated platform for gathering, organising, tracking, and disseminating competitive information on the web. FOCI builds personalised information portfolios through a novel method called User-Configurable Clustering, which allows a user to personalise his/her portfolios in terms of the content as well as the organisational structure. This paper outlines the key challenges we face in personalised information management and gives a detailed account of FOCI's underlying personalisation mechanism. For a quantitative evaluation of the system's performance, we propose a set of performance indices based on information entropy that measures the degree of matching between a system-generated cluster structure and a user-preferred category organisation. Experimental results of a case study show that FOCI's personalisation increases the degree of matching tremendously after a reasonable number of operations. In addition, the personalised portfolios can be used to track and organise new information with a good level of performance.