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A path-oriented matrix-based knowledge representation systemExperience has shown that designing a good representation is often the key to turning hard problems into simple ones. Most AI (Artificial Intelligence) search/representation techniques are oriented toward an infinite domain of objects and arbitrary relations among them. In reality much of what needs to be represented in AI can be expressed using a finite domain and unary or binary predicates. Well-known vector- and matrix-based representations can efficiently represent finite domains and unary/binary predicates, and allow effective extraction of path information by generalized transitive closure/path matrix computations. In order to avoid space limitations a set of abstract sparse matrix data types was developed along with a set of operations on them. This representation forms the basis of an intelligent information system for representing and manipulating relational data.
Document ID
Document Type
Contractor Report (CR)
Feyock, Stefan
(College of William and Mary Williamsburg, VA, United States)
Karamouzis, Stamos T.
(College of William and Mary Williamsburg, VA, United States)
Date Acquired
September 6, 2013
Publication Date
September 1, 1993
Publication Information
Publisher: NASA
Subject Category
Computer Programming And Software
Report/Patent Number
NAS 1.26:4539
Accession Number
Funding Number(s)
PROJECT: RTOP 505-64-13-22
Distribution Limits
Work of the US Gov. Public Use Permitted.
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