Abstract

We report on our experience in developing a query-answering system that integrates multiple knowledge sources. The system is based on a novel architecture for combining knowledge sources in which the sources can produce new subgoals as well as ground facts in the search for answers to existing subgoals. The system uses a query planner that takes into account different query-processing capabilities of individual sources and augments them gracefully. A reusable ontology provides a mediated schema that serves as the basis for integration. We have evaluated the system on a suite of test queries in a realistic application to verify the practicality of our approach.

Date

July 16, 2006

Authors

José Luis Ambite, Vinay K Chaudhri, Richard Fikes, Jessica Jenkins, Sunil Mishra, Maria Muslea, Tomas Uribe, Guizhen Yang

Journal

Proceedings of the National Conference on Artificial Intelligence

Volume

21

Issue

2

Pages

1751

Publisher

Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999