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Automated Extraction of System Structure Knowledge From Text

[+] Author Affiliations
Hyunmin Cheong, Wei Li, Francesco Iorio

Autodesk Research, Toronto, ON, Canada

Paper No. DETC2016-59551, pp. V02AT03A011; 10 pages
doi:10.1115/DETC2016-59551
From:
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2A: 42nd Design Automation Conference
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5010-7
  • Copyright © 2016 by ASME

abstract

This paper presents a method to automatically extract structure knowledge of mechanical systems from natural language text. The current work extends our prior work on extracting function knowledge from text, which was presented at last year’s conference. The method uses rules based on a combination of syntactic, lexical, and redundancy information to identify structure knowledge from parsed text. Three case studies were conducted to evaluate the method. The case studies involved extracting physical connections among a known set of components of a bicycle frame, an internal combustion engine, and a drum brake from Wikipedia. The current work makes progress toward addressing the challenge of knowledge acquisition for knowledge-based CAD systems.

Copyright © 2016 by ASME

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