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

Abstract

The European Union (EU) aims to increase the efficiency and productivity of the construction industry. The EU suggests pairing Building Information Modeling with other digitalization technologies to seize the full potential of the digital transition. Meanwhile, industrial applications of Natural Language Processing (NLP) have emerged. The growth of NLP is affecting the construction industry. However, the potential of NLP and the combination of an NLP and BIM approach is still unexplored. The study tries to address this lack by applying a scientometric analysis to explore the state of the art of NLP in the AECO sector, and the combined applications of NLP and BIM. Science mapping is used to analyze 254 bibliographic records from Scopus Database analyzing the structure and dynamics of the domain by drawing a picture of the body of knowledge. NLP in AECO, and its pairing 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 Automated Compliance Checking and semantic BIM enrichment goals. Artificial intelligence, learning algorithms, and ontologies emerge as the most widespread and promising technological drivers.