@inproceedings{71c466a98c1e4e39a7a976bf79a1dd15,
title = "Reduction methods for design rationale knowledge model",
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{\textquoteright} 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{\textquoteright} collaborative design.",
keywords = "Collaborative design, Design rationale knowledge, Semantic reduction, Structure reduction",
author = "Jiaji Wang and Jihong Liu",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 15th International Conference on Cooperative Design, Visualization, and Engineering, CDVE 2018 ; Conference date: 21-10-2018 Through 24-10-2018",
year = "2018",
doi = "10.1007/978-3-030-00560-3\_29",
language = "英语",
isbn = "9783030005597",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "217--224",
editor = "Yuhua Luo",
booktitle = "Cooperative Design, Visualization, and Engineering - 15th International Conference, CDVE 2018, Proceedings",
address = "德国",
}