Share:


Text mining-based patent analysis of BIM application in construction

    Xing Pan Affiliation
    ; Botao Zhong Affiliation
    ; Xiaobo Wang Affiliation
    ; Ran Xiang Affiliation

Abstract

As a data tool applicable to the full life-cycle of construction engineering and management, Building Information Modeling (BIM) has great potential for significantly increasing project productivity and performance. Awareness of BIM application hotspots and forecasting its trends can drive innovations in construction field. Using patents as data resources, this study develops an effective framework integrating the citation network analysis and the topic clustering technology to identify BIM application information and forecast its trends. This framework comprises three-step analysis:(1) quantitative characteristic analysis of patent outputs; (2) Social Network Analysis (SNA)-based co-occurrence network analysis; and (3) identification of BIM topics using a Latent Dirichlet Allocation (LDA). Finally, the case demonstrates the effectiveness of this framework contributing to promote technological development and innovation of BIM. The contributions of this study are threefold: (1) an innovative text mining-based framework for BIM patent analysis in construction is developed; (2) patents that have focused on identifying the application hotspots and development trend of BIM in accordance with our developed framework are reviewed; and (3) a signpost for technological development and innovation of BIM is provided.

Keyword : Building Information Modeling (BIM), patent-driven analysis, text mining, Social Network Analysis (SNA), Latent Dirichlet Allocation (LDA), application hotspots and forecasting

How to Cite
Pan, X., Zhong, B., Wang, X., & Xiang, R. (2021). Text mining-based patent analysis of BIM application in construction. Journal of Civil Engineering and Management, 27(5), 303-315. https://doi.org/10.3846/jcem.2021.14907
Published in Issue
Jun 3, 2021
Abstract Views
73
PDF Downloads
58
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Al Hattab, M., & Hamzeh, F. (2015). Using social network theory and simulation to compare traditional versus BIM-lean practice for design error management. Automation in Construction, 52, 59–69. https://doi.org/10.1016/j.autcon.2015.02.014

Altwies, J. E., & Nemet, G. F. (2013). Innovation in the U.S. building sector: An assessment of patent citations in building energy control technology. Energy Policy, 52, 819–831. https://doi.org/10.1016/j.enpol.2012.10.050

Ardito, L., Adda, D., & Petruzzelli, A. M. (2017). Mapping innovation dynamics in the internet of things domain: Evidence from patent analysis. Technological Forecasting and Social Change, 136, 317–330. https://doi.org/10.1016/j.techfore.2017.04.022

Azhar, S. (2011). Building information modeling (BIM): trends, benefits, risks, and challenges for the AEC industry. Leadership & Management in Engineering, 11(3), 241–252. https://doi.org/10.1061/(ASCE)LM.1943-5630.0000127

Batool, K., & Niazi, M. A. (2014). Towards a methodology for validation of centrality measures in complex networks. Plos One, 9(4), 90283. https://doi.org/10.1371/journal.pone.0090283

Bastani, K., Namavari, H., & Shaffer, J. (2018). Latent Dirichlet al. ocation (LDA) for topic modeling of the CFPB consumer complaints. Expert Systems with Applications, 127, 256–271. https://doi.org/10.1016/j.eswa.2019.03.001

Blei, D. M., Kucukelbir, A., & McAuliffe, J. D. (2017). Variational inference: a review for statisticians. Journal of the American Statistical Association, 112(518), 859–877. https://doi.org/10.1080/01621459.2017.1285773

Boshnakoska, D., Chorbev, I., & Davcev, D. (2013). Ontology supported patent search architecture with natural language analysis and fuzzy rules. Advances in Intelligent Systems and Computing, 207, 275–284. https://doi.org/10.1007/978-3-642-37169-1_27

Daim, T., Lai, K. K., Yalcin, H., Alsoubie, F., & Kumar, V. (2020). Forecasting technological positioning through technology knowledge redundancy: Patent citation analysis of IoT, cybersecurity, and Blockchain. Technological Forecasting and Social Change, 161, 120329. https://doi.org/10.1016/j.techfore.2020.120329

Cai, F., Ji, J. M., Jiang, Z. Q., Mu, Z. R., Wu, X., Zheng, W. J., Zhou, W. X., Tu, S. T., & Qian, X. H. (2018). Engineering fronts in 2018. Engineering, 4, 748–753. https://doi.org/10.1016/j.eng.2018.11.004

Griliches, Z. (1990). Patent statistics as economic indicators: A survey. Journal of Economic Literature, 28(4), 1661–1707. https://doi.org/10.3386/w3301

Han, Q., Heimerl, F., Codinafilba, J., Lohmann, S., Wanner, L., & Ertl, T. (2017). Visual patent trend analysis for informed decision making in technology management. World Patent Information, 49, 34–42. https://doi.org/10.1016/j.wpi.2017.04.003

Jia, J., Sun, J., Wang, Z., & Xu, T. (2017). The construction of BIM application value system for residential buildings’ design stage in china based on traditional DBB mode. Procedia Engineering, 180, 851–858. https://doi.org/10.1016/j.proeng.2017.04.246

Johansson, M., Roupé, M., & Bosch-Sijtsema, P. (2015). Realtime visualization of building information models (BIM). Automation in Construction, 54, 69–82. https://doi.org/10.1016/j.autcon.2015.03.018

Hatala, J.-P., & Lutta, J. G. (2009). Managing information sharing within an organizational setting: A social network perspective. Performance Improvement Quarterly, 21(4), 5–33. https://doi.org/10.1016/j.autcon.2015.03.018

Ju, Y., & Sohn, S. Y. (2015). Patent-based QFD framework development for identification of emerging technologies and related business models: A case of robot technology in Korea. Technological Forecasting and Social Change, 94, 44–64. https://doi.org/10.1016/j.techfore.2014.04.015

Kang, B. (2014). The innovation process of Huawei and ZTE: Patent data analysis. China Economic Review, 36, 378–393. https://doi.org/10.1016/j.chieco.2014.12.003

Kim, G., & Bae, J. (2017). A novel approach to forecast promising technology through patent analysis. Technological Forecasting and Social Change, 117, 228–237. https://doi.org/10.1016/j.techfore.2016.11.023

Kim, Y. G., Suh, J. H., & Park, S. C. (2008). Visualization of patent analysis for emerging technology. Expert Systems with Applications, 34(3), 1804–1812. https://doi.org/10.1016/j.eswa.2007.01.033

Kim, B. S., Chang, S., & Suh, Y. (2018). Text analytics for classifying types of accident occurrence using accident report documents. Journal of the Korean Society of Safety, 33(3), 58–64. https://doi.org/10.14346/JKOSOS.2018.33.3.58

Krebs, V. E. (2002). Mapping networks of terrorist cells. Connections, 24(3), 43–52.

Li, N., & Wu, D. D. (2010). Using text mining and sentiment analysis for online forums hotspot detection and forecast. Decision Support Systems, 48(2), 354–368. https://doi.org/10.1016/j.dss.2009.09.003

Li, X., Xie, Q., Daim, T., & Huang, L. (2019a). Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology. Technological Forecasting and Social Change, 146, 432–449. https://doi.org/10.1016/j.techfore.2019.01.012

Li, J., Greenwood, D., & Kassem, M. (2019b). Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases. Automation in Construction, 102, 288–307. https://doi.org/10.1016/j.autcon.2019.02.005

Li, X., Fan, M., Zhou, Y., Fu, J., Yuan, F., & Huang, L. (2020). Monitoring and forecasting the development trends of nanogenerator technology using citation analysis and text mining. Nano Energy, 71, 104636. https://doi.org/10.1016/j.nanoen.2020.104636

Liu, Z., Jiang, L., Osmani, M., & Demian, P. (2019). Building Information Management (BIM) and Blockchain (BC) for sustainable building design information management framework. Electronics, 8(7), 724. https://doi.org/10.3390/electronics8070724

Lu, Y., Wu, Z., Chang, R., & Li, Y. (2017). Building Information Modeling (BIM) for green buildings: A critical review and future directions. Automation in Construction, 83, 134–148. https://doi.org/10.1016/j.autcon.2017.08.024

Isikdag, U. (2015). BIM and IoT: A synopsis from GIS perspective. The International Archives of the Photogrammetry, 10, 28–30. https://doi.org/10.5194/isprsarchives-XL-2-W4-33-2015

Markatou, M., & Vetsikas, A. (2015). Innovation and crisis: An analysis of its impact on the Greek patenting activity. Procedia-Social and Behavioral Sciences, 195, 123–132. https://doi.org/10.1016/j.sbspro.2015.06.419

Mcaleer, M., & Slottje, D. (2005). A new measure of innovation: The patent success ratio. Scientometrics, 63(3), 421–429. https://doi.org/10.1007/s11192-005-0222-2

Miettinen, R., & Paavola, S. (2014). Beyond the BIM utopia: Approaches to the development and implementation of building information modeling. Automation in Construction, 43(7), 84–91. https://doi.org/10.1016/j.autcon.2014.03.009

Mignard, C., & Nicolle, C. (2014). Merging BIM and GIS using ontologies application to urban facility management in ACTIVe3D. Computers in Industry, 65(9), 1276–1290. https://doi.org/10.1016/j.compind.2014.07.008

Mohd, S., & Ahmad Latiffi, A. (2013). Building Information Modeling (BIM) application in construction planning. In Seventh International Conference on Construction in the 21st Century (CITC-VII), Bangkok, Thailand. https://doi.org/10.14455/ISEC.res.2014.79

Park, C. S., Lee, D.-Y., Kwon, O.-S., & Wang, X. (2013). A framework for proactive construction defect management using BIM, augmented reality and ontology-based data collection template. Automation in Construction, 33, 61–71. https://doi.org/10.1016/j.autcon.2012.09.010

Perng, Y. H., & Huang, Y. Y. (2016). Investigation of technological trends in shading devices through patent analysis. Journal of Civil Engineering and Management, 22(6), 818–830. https://doi.org/10.3846/13923730.2014.914091

Pilkington, A., Lee, L. L., Chan, C. K., & Ramakrishna, S. (2009). Defining key inventors: A comparison of fuel cell and nanotechnology industries. Technological Forecasting and Social Change, 76(1), 118–127. https://doi.org/10.1016/j.techfore.2008.03.015

Seo, J. O., Han, S. U., Lee, S. H., & Kim, H. (2015). Computer vision techniques for construction safety and health monitoring. Advanced Engineering Informatics, 29(2), 239–251. https://doi.org/10.1016/j.aei.2015.02.001

Sharma, P., & Tripathi, R. C. (2017). Patent citation: a technique for measuring the knowledge flow of information and innovation. World Patent Information, 51, 31–42. https://doi.org/10.1016/j.wpi.2017.11.002

Sheikh, N. J., & Sheikh, O. (2017). Forecasting of biosensor technologies for emerging point of care and medical IoT applications using bibliometrics and patent analysis. Portland International Conference on Management of Engineering and Technology (pp. 3082–3093), Portland, USA. https://doi.org/10.1109/PICMET.2016.7806585

Sheng, D., Ding, L., Zhong, B. T., Love, P. E. D., & Chen, J. G. (2020). Construction quality information management with blockchains. Automation in Construction, 120, 103373. https://doi.org/10.1016/j.autcon.2020.103373

Sohrabi, B., Vanani, I. R., & Abedin, E. (2018). Human resources management and information systems trend analysis using text clustering. International Journal of Human Capital and Information Technology Professionals, 9(3). https://doi.org/10.4018/ijhcitp.2018070101

Turk, Z., & Klinc, R. (2017). Potentials of blockchain technology for construction management. Procedia Engineering, 196, 638–645. https://doi.org/10.1016/j.proeng.2017.08.052

Volk, R., Stengel, J., & Schultmann, F. (2014). Building Information Modeling (BIM) for existing buildings—literature review and future needs. Automation in Construction, 38, 109–127. https://doi.org/10.1016/j.autcon.2013.10.023

Wang, Y. B., & Xu, W. (2018). Leveraging deep learning with LDA-based text analytics to detect automobile insurance fraud. Decision Support Systems, 105, 87–95. https://doi.org/10.1016/j.dss.2017.11.001

Yang, J. M., Liao, W. C., Wu, W. C., Yin, & C. Y. (2009). Trend analysis of machine learning-A text mining and document clustering methodology. In Proceedings-2009 International Conference on New Trends in Information and Service Science, NISS 2009 (pp. 481–485). https://doi.org/10.1109/NISS.2009.176

Ye, Z., Yin, M., Tang, L., & Jiang, H. (2018). Cup-of-Water theory: A review on the interaction of BIM, IoT and blockchain during the whole building lifecycle. In Proceedings of the 35th International Symposium on Automation and Robotics in Construction (ISARC 2018), Berlin, Germany. https://doi.org/10.22260/isarc2018/0066

Yoon, J., Choi, S., & Kim, K. (2011). Invention property-function network analysis of patents: A case of silicon-based thin film solar cells. Scientometrics, 86(3), 687–703. https://doi.org/10.1007/s11192-010-0303-8

You, H., Li, M., Hipel, K. W., Jiang, J., Ge, B., & Duan, H. (2017). Development trend forecasting for coherent light generator technology based on patent citation network analysis. Scientometrics, 111(1), 297–315. https://doi.org/10.1007/s11192-017-2252-y

Zhang, L. (2011). Identifying key technologies in Saskatchewan, Canada: Evidence from patent information. World Patent Information, 33(4), 364–370. https://doi.org/10.1016/j.wpi.2011.06.002

Zhang, Y., Guo, S. L., Han, L.N., & Li, T. L. (2016). Application and exploration of big data mining in clinical medicine. Journal of China Medicine, 129(6), 731–738. https://doi.org/10.4103/0366-6999.178019

Zhong, B. T., Hei, Y. J., Li, H., Rose, T., & Luo, H. B. (2019). Patent cooperative patterns and development trends of Chinese construction enterprises: A network analysis. Journal of Civil Engineering and Management, 25(3), 228–240. https://doi.org/10.3846/jcem.2019.8137

Zhong, B. T., Pan, X., Love, P. E. D., Ding, L. Y., & Fang, W. (2020). Deep learning and network analysis: classifying and visualizing accident narratives in construction. Automation in Construction, 113, 103089. https://doi.org/10.1016/j.autcon.2020.103089