Concept Learning for Achieving Personalized Ontologies: An Active Learning Approach

In many multiagent approaches, it is usual to assume the existence of a common ontology among agents. However, in dynamic systems, the existence of such an ontology is unrealistic and its maintenance is cumbersome. Burden of maintaining a common ontology can be alleviated by enabling agents to evolve their ontologies personally. However, with different ontologies, agents are likely to run into communication problems since their vocabularies are different from each other. Therefore, to achieve personalized ontologies, agents must have a means to understand the concepts used by others. Consequently, this paper proposes an approach that enables agents to teach each other concepts from their ontologies using examples. Unlike other concept learning approaches, our approach enables the learner to elicit most informative examples interactively from the teacher. Hence, the learner participates to the learning process actively. We empirically compare the proposed approach with the previous conc...

• Type: Conference
• Year: 2009
• Where: ADMI
• Authors: Murat Sensoy, Pinar Yolum
• Keywords: ADMI 2009, Common Ontology, Concept Learning Approaches, Data Mining, Multiagent Approaches