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Data mining in the construction industry: Present status, opportunities, and future trends
Abstract The construction industry is experiencing remarkable growth in the data generation. Data mining (DM) from considerable amount of data in the construction industry has emerged as an important tool for knowledge discovery. Despite the remarkable growth of DM applications to the construction industry, a systematic review on DM applications in this field is still lacking. Therefore, this paper attempts to provide a comprehensive literature review of DM application articles published between 2001 and 2019 with the specificity of construction industry. The popularity of DM applications in the construction industry is increasing, especially after 2016, with a plurality emanating from China. The main data sources, DM functions, and frequently used DM techniques in the construction industry are discussed in detail. Nine major application fields are identified, with the primary research interests focusing on multiple dimensions of energy, safety management, building occupancy and occupant behavior, material performance, and textual knowledge discovery. Four major challenges and four future research directions are proposed by drawing on the research findings. This study provides academics and practitioners with a more comprehensive understanding of the state-of-the-art of DM applications and heuristic implications for future studies.
Highlights A comprehensive review of data mining (DM) application in construction industry from 2001 to March 2019 is conducted. The popularity of DM applications in construction industry is increasing, especially after 2016. 9 major application fields are identified and comprehensively analyzed. Four challenges and four future directions are proposed.
Data mining in the construction industry: Present status, opportunities, and future trends
Abstract The construction industry is experiencing remarkable growth in the data generation. Data mining (DM) from considerable amount of data in the construction industry has emerged as an important tool for knowledge discovery. Despite the remarkable growth of DM applications to the construction industry, a systematic review on DM applications in this field is still lacking. Therefore, this paper attempts to provide a comprehensive literature review of DM application articles published between 2001 and 2019 with the specificity of construction industry. The popularity of DM applications in the construction industry is increasing, especially after 2016, with a plurality emanating from China. The main data sources, DM functions, and frequently used DM techniques in the construction industry are discussed in detail. Nine major application fields are identified, with the primary research interests focusing on multiple dimensions of energy, safety management, building occupancy and occupant behavior, material performance, and textual knowledge discovery. Four major challenges and four future research directions are proposed by drawing on the research findings. This study provides academics and practitioners with a more comprehensive understanding of the state-of-the-art of DM applications and heuristic implications for future studies.
Highlights A comprehensive review of data mining (DM) application in construction industry from 2001 to March 2019 is conducted. The popularity of DM applications in construction industry is increasing, especially after 2016. 9 major application fields are identified and comprehensively analyzed. Four challenges and four future directions are proposed.
Data mining in the construction industry: Present status, opportunities, and future trends
Yan, Hang (author) / Yang, Nan (author) / Peng, Yi (author) / Ren, Yitian (author)
2020-06-13
Article (Journal)
Electronic Resource
English
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