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Representing Complex Physical Objects in Memory

Wasserman, Kenneth; Lebowitz, Michael

Researchers an artificial intelligence have proposed and implemented several representation systems for use in computer programs that "understand" natural language input. Noticeably lacking from these systems is a robust and concise method of representing complex physical objects. This paper describes a language independent scheme for encoding real-world objects in a manner that captures elements of how people describe them. Two major groups of objects are distinguished: ''unitary'' objects that are described by a single "shape-descriptor"; and "composite" objects that are represented by a frame-based system that focuses on the physical relations that exist among obiects. The heart of this scheme is a primitive-based framework that classifies physical relations into three fundamental categories with five possible properties. Our current work on RESEARCHER, a program that employs this scheme while reading patent abstracts, is also discussed.

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Academic Units
Computer Science
Publisher
Department of Computer Science, Columbia University
Series
Columbia University Computer Science Technical Reports, CUCS-037-82
Published Here
October 26, 2011