During the 1970s, a number of systems providing limited English-language processing capabilities were developed to permit computer access by casual or untrained users. Our interest is in adapting and extending techniques developed for these systems, especially those used in database query systems and our own English-language programming language system (NLC), for use in office environments. This paper describes the Layered Domain Class system (LDC), a state-of-the-art natural language processor whose major goals are (1) to provide English-language retrieval capabilities for mediumsized office domains that have been stored on the computer as text-edited files, as opposed to more restrictive database structures; and (2) to eliminate the need to call in the system designer when extensions into new domains are desired, without sacrificing the depth or reliability of the interface. In this paper we (a) provide an overview of LDC, including sample inputs; (b) briefly discuss the role of each module of the system, with special attention to provisions for users to adapt the system to deal with new types of data; and (c) consider the relation of our system to other formal and natural language interfaces that are in use or under development.
Artificial intelligence textbooks present concepts, history and examples, but they do not always have time for lengthy discussions of methods and tools for solving the kinds of programming problems that arise in artificial intelligence. Kreutzer and McKenzie have written a book to fill this gap. Their book aids those who must solve practical problems, by providing three kinds of information for the AI programmer. First, the authors describe some programming languages well-suited for AI problems. Next, they summarize several of the commonly-used approaches to AI problem solving. Finally, they give source code for an AI programming "toolbox."
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