A logic to unify semantic network knowledge systems with object-oriented database models

In recent years, coupling knowledge-based systems with existing database systems has gained tremendous attention in both artificial intelligence and database communities. However, many existing approaches suffer from (1) poor support of the semantic modeling capabilities in the underlying relational database systems that is required by the coupled knowledge systems; (2) inadequate performance due to the separation of inference engines from database engines; (3) weak knowledge consistency due to the separation of data and knowledge stored in different domains. The author takes a novel approach by tightly coupling semantic-network based knowledge systems with object-oriented database models. In order to support the highly semantic knowledge-based system, he augments existing object-oriented data models with extra modeling capabilities, such as the interaction of generalization/specialization with aggregation and other association relationships in semantic nets. All semantic information is transformed and encoded into first-order logic representation for efficient reasoning.<
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