Text Mining-Based Patent Analysis for Automated Rule Checking in AEC
19th International Conference on Computing in Civil and Building Engineering (ICCCBE 2022), 2022
引用方式: Zheng, Z., Kang, B.R., Yuan, Q.T., Zhou, Y.C., Lu, X.Z., Lin, J.R.* (2022). Text Mining-Based Patent Analysis for Automated Rule Checking in AEC. 19th International Conference on Computing in Civil and Building Engineering (ICCCBE 2022), xxx-xxx. Cape Town, South Africa. https://doi.org/10.48550/arXiv.2212.05891
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.
The authors are grateful for the financial support received from the National Natural Science Foundation of China (No. 51908323, No. 72091512), the National Key R&D Program (No. 2019YFE0112800), and the Tencent Foundation through the XPLORER PRIZE.