Citation:
Deng Langni, Lai Shijin, Wu Ting, Liao Ling, Zhong Mengjun. Research on BIM Academic Hot Spots and Trend Analysis Methods Based on Data Mining Technology. Journal of Information Technologyin Civil Engineering and Architecture,
2019, 11(6): 1-10.
doi: 10.16670/j.cnki.cn11-5823/tu.2019.06.01
2019, 11(6): 1-10. doi: 10.16670/j.cnki.cn11-5823/tu.2019.06.01
Research on BIM Academic Hot Spots and Trend Analysis Methods Based on Data Mining Technology
| 1. | School of Civil Engineering and Architecture, Guangxi University of Science and Technology, Liuzhou 545006, China |
| 2. | BIM Research Center, Guangxi University of Science and Technology, Liuzhou 545006, China |
Researchers always face a problem of how to better analyze and understand the BIM academic hot spots and trends. This paper proposes a method based on data mining technology to better analyze the BIM academic hot spots and trends, which uses SATI, Ucinet and Cite Space software to process bibliographic information. By mining and analyzing data from different forms and perspectives, the hidden laws of data information can be discovered, assisting relevant personnels to understand the academic hot spots and trends of BIM. In the paper, the method is described from three aspects of data extraction and processing, BIM academic hot spot analysis, and BIM academic trend analysis. In order to test the practicability of the method, the method is applied to the literature data analysis of BIM academic conference. Results show that the method is able to make different software complementary. And conclusions are made that current BIM researches mainly focus on data transformation and automatic modeling based on IFC Standard, BIM and PC building, etc., and that the future research focuses of BIM will turn to the academic development trend of basic research.
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