Seonghyeon Moon

648 total citations
21 papers, 412 citations indexed

About

Seonghyeon Moon is a scholar working on Building and Construction, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Seonghyeon Moon has authored 21 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Building and Construction, 6 papers in Artificial Intelligence and 6 papers in Management Science and Operations Research. Recurrent topics in Seonghyeon Moon's work include BIM and Construction Integration (8 papers), Construction Project Management and Performance (5 papers) and Occupational Health and Safety Research (5 papers). Seonghyeon Moon is often cited by papers focused on BIM and Construction Integration (8 papers), Construction Project Management and Performance (5 papers) and Occupational Health and Safety Research (5 papers). Seonghyeon Moon collaborates with scholars based in South Korea, Singapore and United States. Seonghyeon Moon's co-authors include Seokho Chi, Bon‐Gang Hwang, Madhav Nepal, Hao Zhang, Jay Yang, Jung-Hoon Kim, Mubbasir Kapadia, Vladimir Pavlović, Sejong Yoon and Shuyi Wang and has published in prestigious journals such as Automation in Construction, Journal of Construction Engineering and Management and Advanced Engineering Informatics.

In The Last Decade

Seonghyeon Moon

19 papers receiving 397 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Seonghyeon Moon South Korea 10 137 126 111 109 72 21 412
Tuyen Le United States 12 211 1.5× 154 1.2× 103 0.9× 155 1.4× 83 1.2× 45 496
JeeHee Lee United States 9 188 1.4× 106 0.8× 65 0.6× 160 1.5× 27 0.4× 27 397
Na Xu China 12 151 1.1× 237 1.9× 59 0.5× 131 1.2× 59 0.8× 28 527
Dean Bowman United States 3 165 1.2× 402 3.2× 72 0.6× 119 1.1× 147 2.0× 3 604
Nima Gerami Seresht Canada 12 157 1.1× 83 0.7× 43 0.4× 193 1.8× 47 0.7× 28 366
Z. Ren United Kingdom 10 211 1.5× 31 0.2× 113 1.0× 203 1.9× 26 0.4× 21 439
Jingyang Zhou Australia 11 204 1.5× 53 0.4× 24 0.2× 119 1.1× 69 1.0× 26 392
Daniel P. de Oliveira United States 10 124 0.9× 37 0.3× 24 0.2× 153 1.4× 84 1.2× 23 329
Liangliang Song China 13 94 0.7× 155 1.2× 15 0.1× 68 0.6× 78 1.1× 23 463
Hala Nassereddine United States 12 244 1.8× 71 0.6× 16 0.1× 122 1.1× 52 0.7× 72 481

Countries citing papers authored by Seonghyeon Moon

Since Specialization
Citations

This map shows the geographic impact of Seonghyeon Moon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Seonghyeon Moon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seonghyeon Moon more than expected).

Fields of papers citing papers by Seonghyeon Moon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seonghyeon Moon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Seonghyeon Moon. The network helps show where Seonghyeon Moon may publish in the future.

Co-authorship network of co-authors of Seonghyeon Moon

This figure shows the co-authorship network connecting the top 25 collaborators of Seonghyeon Moon. A scholar is included among the top collaborators of Seonghyeon Moon based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Seonghyeon Moon. Seonghyeon Moon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Shuyi, Seonghyeon Moon, Yuguang Fu, & Jinwoo Kim. (2025). Construction regulatory document digitalization with layout knowledge-informed object detection and semantic text recognition. Advanced Engineering Informatics. 65. 103278–103278. 1 indexed citations
4.
Moon, Seonghyeon, et al.. (2023). MSI: Maximize Support-Set Information for Few-Shot Segmentation. 19209–19219. 16 indexed citations
5.
Moon, Seonghyeon, et al.. (2023). Comparing natural language processing (NLP) applications in construction and computer science using preferred reporting items for systematic reviews (PRISMA). Automation in Construction. 154. 105020–105020. 31 indexed citations
6.
Moon, Seonghyeon, et al.. (2023). Development of a real-time noise estimation model for construction sites. Advanced Engineering Informatics. 58. 102133–102133. 9 indexed citations
7.
Moon, Seonghyeon, et al.. (2022). Real-Time Construction Site Noise Mapping System Based on Spatial Interpolation. Journal of Management in Engineering. 39(2). 4 indexed citations
8.
Moon, Seonghyeon, et al.. (2022). Automated detection of contractual risk clauses from construction specifications using bidirectional encoder representations from transformers (BERT). Automation in Construction. 142. 104465–104465. 73 indexed citations
9.
Moon, Seonghyeon, et al.. (2022). Feasibility Study of a BERT-based Question Answering Chatbot for Information Retrieval from Construction Specifications. 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). 970–974. 5 indexed citations
10.
Moon, Seonghyeon, et al.. (2022). Reference section identification of construction specifications by a deep structured semantic model. Engineering Construction & Architectural Management. 30(9). 4358–4386. 7 indexed citations
11.
Moon, Seonghyeon, et al.. (2021). Automated system for construction specification review using natural language processing. Advanced Engineering Informatics. 51. 101495–101495. 39 indexed citations
12.
Moon, Seonghyeon, et al.. (2021). Semantic text-pairing for relevant provision identification in construction specification reviews. Automation in Construction. 128. 103780–103780. 25 indexed citations
13.
Chi, Seokho, et al.. (2021). Internal Communication Effectiveness Model for Construction Companies: A Case Study of the Korean Construction Industry. KSCE Journal of Civil Engineering. 25(12). 4520–4534. 7 indexed citations
14.
Moon, Seonghyeon, et al.. (2020). Automated Construction Specification Review with Named Entity Recognition Using Natural Language Processing. Journal of Construction Engineering and Management. 147(1). 72 indexed citations
15.
Moon, Seonghyeon, et al.. (2020). Bridge Damage Recognition from Inspection Reports Using NER Based on Recurrent Neural Network with Active Learning. Journal of Performance of Constructed Facilities. 34(6). 30 indexed citations
16.
Moon, Seonghyeon, et al.. (2019). Automatic Review of Construction Specifications Using Natural Language Processing. 401–407. 9 indexed citations
17.
Moon, Seonghyeon, et al.. (2018). Topic Modeling of News Article about International Construction Market Using Latent Dirichlet Allocation. Journal of the Korean Society of Civil Engineers. 38(4). 595–599. 1 indexed citations
18.
Moon, Seonghyeon, et al.. (2018). Document Management System Using Text Mining for Information Acquisition of International Construction. KSCE Journal of Civil Engineering. 22(12). 4791–4798. 25 indexed citations
19.
Moon, Seonghyeon, et al.. (2017). Predicting Construction Cost Index Using the Autoregressive Fractionally Integrated Moving Average Model. Journal of Management in Engineering. 34(2). 16 indexed citations
20.
Zhang, Hao, Seokho Chi, Jay Yang, Madhav Nepal, & Seonghyeon Moon. (2016). Development of a Safety Inspection Framework on Construction Sites Using Mobile Computing. Journal of Management in Engineering. 33(3). 37 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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