A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Application of Spreading Activation Techniques in InformationRetrieval
Artificial Intelligence Review
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IEEE Transactions on Knowledge and Data Engineering
Ontology-based personalized search and browsing
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A Collaborative Ontology-Based User Profiles System
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IEEE Transactions on Knowledge and Data Engineering
Semantic spam filtering from personalized ontologies
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Semantic similarity estimation from multiple ontologies
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Strategies for avoiding preference profiling in agent-based e-commerce environments
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Representing and Reasoning About XML with Ontologies
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Statistical user model supported by R-Tree structure
Applied Intelligence
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Personal agents gather information about users in a user profile. In this work, we propose a novel ontology-based user profile learning. Particularly, we aim to learn context-enriched user profiles using data mining techniques and ontologies. We are interested in knowing to what extent data mining techniques can be used for user profile generation, and how to utilize ontologies for user profile improvement. The objective is to semantically enrich a user profile with contextual information by using association rules, Bayesian networks and ontologies in order to improve agent performance. At runtime, we learn which the relevant contexts to the user are based on the user's behavior observation. Then, we represent the relevant contexts learnt as ontology segments. The encouraging experimental results show the usefulness of including semantics into a user profile as well as the advantages of integrating agents and data mining using ontologies.