Cargando…
Overview and analysis of the text mining applications in the construction industry
The data generation in the construction industry has increased dramatically. The major portion of the data in the architecture, engineering and construction (AEC) domain are unstructured textual documents. Text mining (TM) has been introduced to the construction industry to extract underlying knowle...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730136/ https://www.ncbi.nlm.nih.gov/pubmed/36506381 http://dx.doi.org/10.1016/j.heliyon.2022.e12088 |
_version_ | 1784845603272916992 |
---|---|
author | Yan, Hang Ma, Mingxue Wu, Ying Fan, Hongqin Dong, Chao |
author_facet | Yan, Hang Ma, Mingxue Wu, Ying Fan, Hongqin Dong, Chao |
author_sort | Yan, Hang |
collection | PubMed |
description | The data generation in the construction industry has increased dramatically. The major portion of the data in the architecture, engineering and construction (AEC) domain are unstructured textual documents. Text mining (TM) has been introduced to the construction industry to extract underlying knowledge from unstructured data. However, few articles have comprehensively reviewed applications of TM in the AEC domain. Thus, this study adopts a qualitative-quantitative method to conduct a state-of-the-art survey on the articles related to applications of TM in the construction industry which published between the year of 2000 and 2021. VOSviewer software was applied to provide an overview of TM applications regarding to the publication trend, active countries and regions, productive authors, and co-occurrence of keywords perspectives. Eight prime application fields of TM were discussed and analyzed in detail. Five key challenges and three future directions have been proposed. This review can help the research community to grasp the state-of-the-art of TM applications in the construction industry and identify the directions of further research. |
format | Online Article Text |
id | pubmed-9730136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97301362022-12-09 Overview and analysis of the text mining applications in the construction industry Yan, Hang Ma, Mingxue Wu, Ying Fan, Hongqin Dong, Chao Heliyon Review Article The data generation in the construction industry has increased dramatically. The major portion of the data in the architecture, engineering and construction (AEC) domain are unstructured textual documents. Text mining (TM) has been introduced to the construction industry to extract underlying knowledge from unstructured data. However, few articles have comprehensively reviewed applications of TM in the AEC domain. Thus, this study adopts a qualitative-quantitative method to conduct a state-of-the-art survey on the articles related to applications of TM in the construction industry which published between the year of 2000 and 2021. VOSviewer software was applied to provide an overview of TM applications regarding to the publication trend, active countries and regions, productive authors, and co-occurrence of keywords perspectives. Eight prime application fields of TM were discussed and analyzed in detail. Five key challenges and three future directions have been proposed. This review can help the research community to grasp the state-of-the-art of TM applications in the construction industry and identify the directions of further research. Elsevier 2022-12-05 /pmc/articles/PMC9730136/ /pubmed/36506381 http://dx.doi.org/10.1016/j.heliyon.2022.e12088 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Article Yan, Hang Ma, Mingxue Wu, Ying Fan, Hongqin Dong, Chao Overview and analysis of the text mining applications in the construction industry |
title | Overview and analysis of the text mining applications in the construction industry |
title_full | Overview and analysis of the text mining applications in the construction industry |
title_fullStr | Overview and analysis of the text mining applications in the construction industry |
title_full_unstemmed | Overview and analysis of the text mining applications in the construction industry |
title_short | Overview and analysis of the text mining applications in the construction industry |
title_sort | overview and analysis of the text mining applications in the construction industry |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730136/ https://www.ncbi.nlm.nih.gov/pubmed/36506381 http://dx.doi.org/10.1016/j.heliyon.2022.e12088 |
work_keys_str_mv | AT yanhang overviewandanalysisofthetextminingapplicationsintheconstructionindustry AT mamingxue overviewandanalysisofthetextminingapplicationsintheconstructionindustry AT wuying overviewandanalysisofthetextminingapplicationsintheconstructionindustry AT fanhongqin overviewandanalysisofthetextminingapplicationsintheconstructionindustry AT dongchao overviewandanalysisofthetextminingapplicationsintheconstructionindustry |