Agents in a Multi-cultural World: Towards Ontological Reconciliation
AI '01 Proceedings of the 14th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Reconciling ontological differences by assistant agents
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
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Communication among heterogeneous information agents is often difficult because they often use different structures to express the same information. A common ontology could resolve this problem. However, it would be very difficult to build such an ontology for dynamic information spaces such as the WWW. Thus, automatic reconciliation of differences is necessary to permit multiagent communication within an open environment where new expressions tend to emerge in communication. We propose a technique that enables automatic mapping of equivalent slots in different frames.The proposed technique, Example-Based Frame Mapping (EBFM), generates hypotheses of equivalent slots, then selects a plausible hypothesis by comparing similarities within the examples inferred to express the same object. EBFM solves the essential problems that arise in frame mapping (e.g., synonyms and homonyms) by using only the available information without requiring any domain-specific heuristic knowledge, and can achieve more than 99% accuracy.