Semantic and structural query reformulation for efficient manipulation of very large knowledge bases

Abstract

The authors present a framework for a knowledge base system that supports complex objects and two-level rules. By assuming that the portion of a rule base that is related to a query is small enough to fit in main memory, the bottleneck of the inference stage is not in unifying or managing complex objects but in identifying relevant rules for the query. However, efficient storage and manipulation of complex objects is critical in the physical database access stage where the fact base consists of large number of general objects. Consequently, the system has been divided into two virtually independent stages. An obvious, application of a two-level rule base is in semantic query optimization, where the integrity constraints will be the semantic rules and application of restrictions from them is optional. By supplying a number of special system predicates, the two-level rule base can be used to control the activities of the knowledge base. The two levels of rules naturally map to rules and meta rules in artificial intelligence applications.<>