Showing papers on "Knowledge extraction published in 1984"

The Logic of Incomplete Knowledge Bases

Abstract: Some formal representation issues underlying the use of incomplete knowledge bases are discussed. An incomplete knowledge base is one that has only partial knowledge of the application domain. It is argued that a language that can refer to both the application domain and to the state of the knowledge base is required to specify and to question an incomplete knowledge base. A formal logical language with this expressive ability is presented and its semantics and proof theory are defined. It is also shown how different the use of the language must be, depending on whether the interaction involves querying or defining the knowledge base.

Database Access Requirements of Knowledge-Based Systems

Abstract: Knowledge bases constitute the core of those Artificial Intelligenceprograms which have come to be known as Expert Systems. Anexamination of the most dominant knowledge representation schemes usedin these systems reveals that a knowledge base can, and possiblyshould, be described at several levels using different schemes,including those traditionally used in operational databases. Thischapter provides evidence that solutions to the organization andaccess problem for very large knowledge bases require the employmentof appropriate database management methods, at least for the lowestlevel of description -- the facts or data. We identify the databaseaccess requirements of knowledge-based or expert systems and thenpresent four general architectural strategies for the design of expertsystems that interact with databases, together with specificrecommendations for their suitability in particular situations. Animplementation of the most advanced and ambitious of these strategiesis then discussed in some detail.

Interactive classification: a technique for building and maintaining knowledge bases

Abstract: The practical application of knowledge-based systems, such as in expert systems, often requires the maintenance of large amounts of declarative knowledge. As a knowledge base grows in size and complexity, it becomes more difficult to maintain and extend. Even someone who is familiar with the representation and the contents of the existing knowledge base may introduce inconsistencies and errors whenever an addition or modification is made. This paper describes an approach to this problem based on a tool called an interactive classifier. An interactive classifier uses the contents of the existing knowledge base and knowledge about its representation to help the maintainer describe new knowledge base objects. The interactive classifier will identify the appropriate taxononomic location for the newly described object and add it to thr knowledge base. The new object is allowed to be a generalization of existing knowledge base objects, enabling the system to learn more about existing obects.

Very-high-level programming of knowledge representation schemes

Abstract: This paper proposes building knowledge-based systems using a programming system based on a very-high-level language. It gives an overview of such a programming system, BC, and shows how BC can be used to implement knowledge representation features, providing as examples, automatic maintenance of inverse links and property inheritance. The specification language of BC can be extended to include a knowledge representation language by describing its knowledge representation features. This permits a knowledge-based program and its knowledge base to be written in the same very-high-level language which allows the knowledge to be more efficiently incorporated into the program as well as making the system as a whole easier to understand and extend.