Starr, Barbara and Chaudhri, Vinay K. and Farquhar, Adam and Waldinger, Richard. Knowledge Intesive Query Processing, in Proceedings of the 5th International Workshop Knowledge Representation Meets Databases (KRDB’98), Seattle, USA, 1997.
Introduction
Innovative query interfaces to knowledge and database systems must go beyond simply returning the re-quested information. They must be capable of producing intentional answers when a description improves the understanding of an answer [Mot94], producing conditional answers when no one answer matches the conditions of a query, and using ontological information in processing a query. They should be able to call upon stand-alone reasoning modules that are most suitable for a given query. When answering a question involves reasoning beyond a simple lookup, the system must be able to explain the answer to the user. We are building a question answering system with these objectives. The heart of the system is a knowledge base (KB) and a collection of reasoning methods. The KB is being constructed by a combination of manual and semiautomatic methods. The reasoning methods include conventional database query process-ing, frame-based reasoning, and full first-order theorem proving. The performance of this system will be tested on the Crisis Management Benchmark (CMB),which defines a collection of queries of interest to a crisis analyst.We begin the paper by a description of the CMB. We describe the architecture of our system and then sketch some design ideas for two of its components. We conclude the paper by listing a few of the research challenges faced in building such a system. The work described in the paper is preliminary and is aimed at suggesting directions for future work rather than at describing in-depth technical results.
Keywords: Artificial Intelligence, Artificial Intelligence Center, AIC
