The European Union (EU) aims to increase the efficiency and productivity of the construc-tion industry. The EU suggests pairing Building Information Modeling with other digitalizationtechnologies to seize the full potential of the digital transition. Meanwhile, industrial applications ofNatural Language Processing (NLP) have emerged. The growth of NLP is affecting the constructionindustry. However, the potential of NLP and the combination of an NLP and BIM approach is stillunexplored. The study tries to address this lack by applying a scientometric analysis to explore thestate of the art of NLP in the AECO sector, and the combined applications of NLP and BIM. Sciencemapping is used to analyze 254 bibliographic records from Scopus Database analyzing the structureand dynamics of the domain by drawing a picture of the body of knowledge. NLP in AECO, and itspairing with BIM domain and applications, are investigated by representing: Conceptual, Intellectual,and Social structure. The highest number of NLP applications in AECO are in the fields of Project,Safety, and Risk Management. Attempts at combining NLP and BIM mainly concern the Auto-mated Compliance Checking and semantic BIM enrichment goals. Artificial intelligence, learningalgorithms, and ontologies emerge as the most widespread and promising technological drivers.

Exploring Natural Language Processing in Construction and Integration with Building Information Modeling: A Scientometric Analysis

Mirko Locatelli;Elena Seghezzi;Laura Pellegrini;Giuseppe Martino Di Giuda
2021-01-01

Abstract

The European Union (EU) aims to increase the efficiency and productivity of the construc-tion industry. The EU suggests pairing Building Information Modeling with other digitalizationtechnologies to seize the full potential of the digital transition. Meanwhile, industrial applications ofNatural Language Processing (NLP) have emerged. The growth of NLP is affecting the constructionindustry. However, the potential of NLP and the combination of an NLP and BIM approach is stillunexplored. The study tries to address this lack by applying a scientometric analysis to explore thestate of the art of NLP in the AECO sector, and the combined applications of NLP and BIM. Sciencemapping is used to analyze 254 bibliographic records from Scopus Database analyzing the structureand dynamics of the domain by drawing a picture of the body of knowledge. NLP in AECO, and itspairing with BIM domain and applications, are investigated by representing: Conceptual, Intellectual,and Social structure. The highest number of NLP applications in AECO are in the fields of Project,Safety, and Risk Management. Attempts at combining NLP and BIM mainly concern the Auto-mated Compliance Checking and semantic BIM enrichment goals. Artificial intelligence, learningalgorithms, and ontologies emerge as the most widespread and promising technological drivers.
2021
computational linguistic; artificial intelligence; semantic; BIM; science mapping; co-occurrence networks
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1191388
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