Concept formation in structured domains
Concept formation knowledge and experience in unsupervised learning
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Automated learning of decision rules for text categorization
ACM Transactions on Information Systems (TOIS)
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
A vector space model for automatic indexing
Communications of the ACM
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Text-Learning and Related Intelligent Agents: A Survey
IEEE Intelligent Systems
Ontology Learning for the Semantic Web
IEEE Intelligent Systems
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Clustering Ontology-Based Metadata in the Semantic Web
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Enriching Information Agents' Knowledge by Ontology Comparison: A Case Study
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Learning knowledge rich user models from the semantic web
UM'03 Proceedings of the 9th international conference on User modeling
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
An information-theoretic external cluster-validity measure
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
User Profiling for Web Page Filtering
IEEE Internet Computing
Modeling of User Interest Based on Its Interaction with a Collaborative Knowledge Management System
Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction
Learning dynamic information needs: A collaborative topic variation inspection approach
Journal of the American Society for Information Science and Technology
Social tagging in recommender systems: a survey of the state-of-the-art and possible extensions
Artificial Intelligence Review
Extraction and classification of user behavior
EUC'07 Proceedings of the 2007 international conference on Embedded and ubiquitous computing
An ontological modelling of user requirements for personalised information provision
Information Systems Frontiers
A knowledge-based model using ontologies for personalized web information gathering
Web Intelligence and Agent Systems
Hierarchical user interest modeling for Chinese web pages
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
Extraction of user profile based on workflow and information flow
Expert Systems with Applications: An International Journal
Mining knowledge demands from information flow
Expert Systems with Applications: An International Journal
Agent and multi-agent applications to support distributed communities of practice: a short review
Autonomous Agents and Multi-Agent Systems
Towards group behavioral reason mining
Expert Systems with Applications: An International Journal
An original usage-based metrics for building a unified view of corporate documents
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
A reference profile ontology for communities of practice
International Journal of Metadata, Semantics and Ontologies
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As more information becomes available on the Web, there has been a crescent interest in effective personalization techniques. Personal agents providing assistance based on the content of Web documents and the user interests emerged as a viable alternative to this problem. Provided that these agents rely on having knowledge about users contained into user profiles, i.e., models of user preferences and interests gathered by observation of user behavior, the capacity of acquiring and modeling user interest categories has become a critical component in personal agent design. User profiles have to summarize categories corresponding to diverse user information interests at different levels of abstraction in order to allow agents to decide on the relevance of new pieces of information. In accomplishing this goal, document clustering offers the advantage that an a priori knowledge of categories is not needed, therefore the categorization is completely unsupervised. In this paper we present a document clustering algorithm, named WebDCC (Web Document Conceptual Clustering), that carries out incremental, unsupervised concept learning over Web documents in order to acquire user profiles. Unlike most user profiling approaches, this algorithm offers comprehensible clustering solutions that can be easily interpreted and explored by both users and other agents. By extracting semantics from Web pages, this algorithm also produces intermediate results that can be finally integrated in a machine-understandable format such as an ontology. Empirical results of using this algorithm in the context of an intelligent Web search agent proved it can reach high levels of accuracy in suggesting Web pages.