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Abstract

Snowy-KBMS, a terminological knowledge-base management system, has been designed as an inte grated AI and database system to support the new and next-generation applications. The system pro vides various capabilities such as modification of a dynamically changing knowledge-base and a sec ondary storage subsystem. In order to support in heritance on a large knowledge base efficiently, we have designed a new strategy called controlled and adaptable attribute search (CAAS). This strategy replicates attributes in the knowledge-base hierar chy to improve the search process. However, at tribute replication can be controlled to balance space and time efficiency. This paper presents the CAAS mechanism in detail and the simulation results of replication effects on I/O and space re quirements.

Keywords

Intelligent information systems knowledge-base systems inheritance sys tems attribute replication controlled and adaptable attribute search CAAS

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Simulation Results for an Adaptable Attribute Replication Mechanism to Support Inheritance in Large Knowledge Bases

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