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Forcing all communicating agents to share a common ontology is infeasible. A group of
people with similar interests usually has its own organizational schemes for documents. This
organization may be in the form of an ontology. Different agents may define very different
ontologies, and the semantics for the same terms may be very different in their ontologies. A
mapping from one agent's ontology to another agent's ontology is required to facilitate
communication between agents.
This project develops a tool for automatic mapping between concepts of two ontologies.
We use a probabilistic approach for ontology mapping by using explicit information in the form of
documents assigned to individual concepts. This approach combines DAML+OIL (for ontology
specification), IR text classification techniques (for raw similarity scores between concepts from
each ontology) and Bayesian reasoning (for mapping generation). User specified landmarks are
used to improve accuracy and efficiency.
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