Please use this identifier to cite or link to this item: doi:10.22028/D291-24885
Title: A heuristic driven chart-parser for attributed node labeled graph grammars and its application to feature recognition in CIM
Author(s): Klauck, Christoph
Mauss, Jakob
Language: English
Year of Publication: 1992
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 1992
SWD key words: Künstliche Intelligenz
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: To integrate CA*-systems with other applications in the CIM world, one principal approach currently under development is the feature recognition process based on graph grammars. It enables any CIM component to recognize the higher-level entities - the so-called features - used in this component out of a lower-data exchange format, which might be the internal representation of a CAD system as well as some standard data exchange format. In this paper we present a 'made-to-measure' parsing algorithm for feature recognition. The heuristic driven chart based bottom up parser analyzes attributed node labeled graphs (representing workpieces) with a (feature-)specific attributed node labeled graph grammar (representing the feature definitions) yielding a high level (qualitative) description of the workpiece in terms of features.
Link to this record: urn:nbn:de:bsz:291-scidok-36425
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 92-43
Date of registration: 25-Jun-2011
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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