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Proceedings Paper

Optical Adjacency Matrix Associative Processor
Author(s): David Casasent; Brian Telfer
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Paper Abstract

A new bidirectional optical associative processor is described for searching a hierarchical database that is stored as an adjacency matrix. The paper discusses how the processor can answer relatively complex queries on a knowledge base when the queries are formulated as combinations of set closures, unions, intersections, and complementations. Thus, a processor that performs general set operations results, as well as a system that can answer various knowledge base queries and guide a knowledge base search. These are new operations for associative processors that increase their utility. This new associative processor operates on entities and their attributes. It can be viewed as a type lattice processor (since the entities and attributes form a hierarchy known as a type lattice), as a closure processor (since it performs closure operations that list all attributes of an entity [or entities] or all entities with a given attribute [or attributes]), or as an adjacency processor (since the connection matrix used stores adjacent associations of attributes and entities).

Paper Details

Date Published: 5 February 1990
PDF: 9 pages
Proc. SPIE 1151, Optical Information Processing Systems and Architectures, (5 February 1990); doi: 10.1117/12.962242
Show Author Affiliations
David Casasent, Carnegie Mellon University (United States)
Brian Telfer, Carnegie Mellon University (United States)


Published in SPIE Proceedings Vol. 1151:
Optical Information Processing Systems and Architectures
Bahram Javidi, Editor(s)

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