Abstract
Design rationale knowledge is to solve problems based on the thinking of designers. It is an important design process knowledge. Design rationale knowledge model is an effective method to obtain and express design rationale. This paper proposes two reduction methods for design rationale knowledge model to improve the efficiency of designers’ reuse of design rationale knowledge model. The structure reduction method introduces quotient space theory to extract design intent - decision structure and building hierarchical structure. The semantic reduction method is based on improved manifolds ranking algorithm. The algorithm ranks the relevance of the design rationale knowledge segments and retains the high-relevance segments to form the core of the design process. The semantic reduction method realizes deletion of redundant information in the design rationale knowledge model, improves collaborative design efficiency. The two methods are verified by developing a prototype system, improving the efficiency of designers’ collaborative design.
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Acknowledgements
This work has been supported by Project of National Science Foundation of China through approval No. 51475027 and No. 51575046.
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Wang, J., Liu, J. (2018). Reduction Methods for Design Rationale Knowledge Model. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2018. Lecture Notes in Computer Science(), vol 11151. Springer, Cham. https://doi.org/10.1007/978-3-030-00560-3_29
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DOI: https://doi.org/10.1007/978-3-030-00560-3_29
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