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dc.contributor.authorKettler, Brianen_US
dc.contributor.authorAndersen, Williamen_US
dc.contributor.authorHendler, Jamesen_US
dc.contributor.authorLuke, Seanen_US
dc.date.accessioned2004-05-31T22:33:04Z
dc.date.available2004-05-31T22:33:04Z
dc.date.created1995-06en_US
dc.date.issued1998-10-15en_US
dc.identifier.urihttp://hdl.handle.net/1903/736
dc.description.abstractParka is a symbolic, semantic network knowledge representation system that takes advantage of the massive parallelism of supercomputers such as the Connection Machine. The Parka language has many of the features of traditional semantic net/frame-based knowledge representation languages but also supports several kinds of rapid parallel inference mechanisms that scale to large knowledge-bases of hundreds of thousands of frames or more. Parka is intended for general-purpose use and has been used thus far to support A.I. systems for case-based reasoning and data mining. This document is a user manual for the current version of Parka, version 3.2. It describes the Parka language and presents some examples of knowledge representation using Parka. Details about the parallel algorithms, implementation, and empirical results are presented elsewhere. (Also cross-referenced as UMIACS-TR-95-68)en_US
dc.format.extent1235179 bytes
dc.format.mimetypeapplication/postscript
dc.language.isoen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-3485en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-95-68en_US
dc.titleUsing the Parka Parallel Knowledge Representation System (Version 3.2)en_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US


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