Interactive Ontology-Based User Knowledge Acquisition: A Case Study

摘要

On the Semantic Web personalization technologies are needed to deal with user diversity. Our research aims at maximising the automation of acquisition of user knowledge, thus providing an effective solution for multi-faceted user modeling. This paper presents an approach to eliciting a user's conceptualization by engaging in an ontology-driven dialog. This is implemented as an OWL-based domain-independent diagnostic agent. We show the deployment of the agent in a use case for personalized management of learning content, which has been evaluated in three studies with users. Currently, the system is being deployed in a cultural heritage domain for personalized recommendation of museum resources.