Comparing natural language processing (NLP) applications in construction and computer science using preferred reporting items for systematic reviews (PRISMA)
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57

초록

Despite the increasing use of natural language processing (NLP) in the construction domain, no systematic comparison has been conducted between NLP applications in construction and the latest advancements in NLP within the computer science domain. Therefore, this study compares NLP studies in these two domains. Firstly, a bibliometric analysis was performed on 55 publications in state-of-the-art NLP studies, which identified four main research areas in NLP. Secondly, a systematic review of 202 NLP studies in construction was conducted, presenting representative application areas of NLP and their current technical status. The results reveal a decreasing technology gap between NLP in construction and the state-of-the-art. However, the comparison also highlighted gaps in application areas and methodologies, and eight future research opportunities were proposed. This review serves as a foundation for future studies that aim to apply state-of-the-art NLP technologies in the construction domain. © 2023 Elsevier B.V.

키워드

Bibliometric analysisNatural language processingNLP methodsNLP tasksPreferred reporting items for systematic reviewsSystematic comparisonVOSViewerAUTOMATED INFORMATION EXTRACTIONRISK-MANAGEMENTSAFETY
제목
Comparing natural language processing (NLP) applications in construction and computer science using preferred reporting items for systematic reviews (PRISMA)
저자
Chung, SehwanMoon, SeonghyeonKim, JunghoonKim, JungyeonLim, SeungmoChi, Seokho
DOI
10.1016/j.autcon.2023.105020
발행일
2023-10
유형
Review
저널명
Automation in Construction
154