Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Text Mining-Based Patent Analysis for Automated Rule Checking in AEC
Automated rule checking (ARC), which is expected to promote the efficiency of the compliance checking process in the architecture, engineering, and construction (AEC) industry, is gaining increasing attention. Throwing light on the ARC application hotspots and forecasting its trends are useful to the related research and drive innovations. Therefore, this study takes the patents from the database of the Derwent Innovations Index database (DII) and China national knowledge infrastructure (CNKI) as data sources and then carried out a three-step analysis including (1) quantitative characteristics (i.e., annual distribution analysis) of patents, (2) identification of ARC topics using a latent Dirichlet allocation (LDA) and, (3) SNA-based co-occurrence analysis of ARC topics. The results show that the research hotspots and trends of Chinese and English patents are different. The contributions of this study have three aspects: (1) an approach to a comprehensive analysis of patents by integrating multiple text mining methods (i.e., SNA and LDA) is introduced; (2) the application hotspots and development trends of ARC are reviewed based on patent analysis; and (3) a signpost for technological development and innovation of ARC is provided.
Text Mining-Based Patent Analysis for Automated Rule Checking in AEC
Automated rule checking (ARC), which is expected to promote the efficiency of the compliance checking process in the architecture, engineering, and construction (AEC) industry, is gaining increasing attention. Throwing light on the ARC application hotspots and forecasting its trends are useful to the related research and drive innovations. Therefore, this study takes the patents from the database of the Derwent Innovations Index database (DII) and China national knowledge infrastructure (CNKI) as data sources and then carried out a three-step analysis including (1) quantitative characteristics (i.e., annual distribution analysis) of patents, (2) identification of ARC topics using a latent Dirichlet allocation (LDA) and, (3) SNA-based co-occurrence analysis of ARC topics. The results show that the research hotspots and trends of Chinese and English patents are different. The contributions of this study have three aspects: (1) an approach to a comprehensive analysis of patents by integrating multiple text mining methods (i.e., SNA and LDA) is introduced; (2) the application hotspots and development trends of ARC are reviewed based on patent analysis; and (3) a signpost for technological development and innovation of ARC is provided.
Text Mining-Based Patent Analysis for Automated Rule Checking in AEC
Lecture Notes in Civil Engineering
Skatulla, Sebastian (Herausgeber:in) / Beushausen, Hans (Herausgeber:in) / Zheng, Zhe (Autor:in) / Kang, Bo-Rui (Autor:in) / Yuan, Qi-Tian (Autor:in) / Zhou, Yu-Cheng (Autor:in) / Lu, Xin-Zheng (Autor:in) / Lin, Jia-Rui (Autor:in)
International Conference on Computing in Civil and Building Engineering ; 2022 ; Cape Town, South Africa
Advances in Information Technology in Civil and Building Engineering ; Kapitel: 2 ; 11-25
30.08.2023
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Apply text mining in analysis of patent document
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