Comparing natural language processing (NLP) applications in construction and computer science using preferred reporting items for systematic reviews (PRISMA)
- Authors
- Chung, Sehwan; Moon, Seonghyeon; Kim, Junghoon; Kim, Jungyeon; Lim, Seungmo; Chi, Seokho
- Issue Date
- Oct-2023
- Publisher
- Elsevier BV
- Keywords
- Bibliometric analysis; Natural language processing; NLP methods; NLP tasks; Preferred reporting items for systematic reviews; Systematic comparison; VOSViewer
- Citation
- Automation in Construction, v.154
- Indexed
- SCIE
SCOPUS
- Journal Title
- Automation in Construction
- Volume
- 154
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/68744
- DOI
- 10.1016/j.autcon.2023.105020
- ISSN
- 0926-5805
1872-7891
- Abstract
- 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.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - 공과대학 > Department of Industrial and Systems Engineering > Journal Articles

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.