Yongmoo Suh

1.1k total citations
43 papers, 784 citations indexed

About

Yongmoo Suh is a scholar working on Artificial Intelligence, Sociology and Political Science and Information Systems. According to data from OpenAlex, Yongmoo Suh has authored 43 papers receiving a total of 784 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 17 papers in Sociology and Political Science and 16 papers in Information Systems. Recurrent topics in Yongmoo Suh's work include Digital Marketing and Social Media (16 papers), Semantic Web and Ontologies (7 papers) and Imbalanced Data Classification Techniques (7 papers). Yongmoo Suh is often cited by papers focused on Digital Marketing and Social Media (16 papers), Semantic Web and Ontologies (7 papers) and Imbalanced Data Classification Techniques (7 papers). Yongmoo Suh collaborates with scholars based in South Korea, United States and Japan. Yongmoo Suh's co-authors include Keunho Choi, Gun-Woo Kim, Donghee Yoo, Hanjun Lee, Jinyoung Han, Jung-Eun Kim, Andrew B. Whinston, Matti Hämäläinen, Clyde W. Holsapple and Namchul Jung and has published in prestigious journals such as Expert Systems with Applications, Decision Support Systems and Journal of the Association for Information Systems.

In The Last Decade

Yongmoo Suh

37 papers receiving 728 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yongmoo Suh South Korea 12 355 266 212 146 91 43 784
Soe‐Tsyr Yuan Taiwan 14 169 0.5× 111 0.4× 212 1.0× 204 1.4× 43 0.5× 67 654
Kaiquan Xu China 13 366 1.0× 593 2.2× 316 1.5× 145 1.0× 26 0.3× 29 1.1k
Jaime Gómez Spain 13 774 2.2× 435 1.6× 104 0.5× 50 0.3× 85 0.9× 36 1.2k
Amit V. Deokar United States 16 363 1.0× 254 1.0× 354 1.7× 110 0.8× 25 0.3× 75 1.1k
Nachiketa Sahoo United States 12 202 0.6× 160 0.6× 225 1.1× 218 1.5× 58 0.6× 34 670
Tony Cheng-Kui Huang Taiwan 18 334 0.9× 208 0.8× 160 0.8× 135 0.9× 26 0.3× 54 937
Gautam Pant United States 18 627 1.8× 301 1.1× 102 0.5× 55 0.4× 49 0.5× 36 941
Elroy Eugene Smith South Africa 13 437 1.2× 196 0.7× 78 0.4× 54 0.4× 24 0.3× 44 810
Victoria Yoon United States 16 201 0.6× 181 0.7× 293 1.4× 196 1.3× 27 0.3× 57 816
Kangning Wei China 12 472 1.3× 99 0.4× 150 0.7× 70 0.5× 40 0.4× 24 1.1k

Countries citing papers authored by Yongmoo Suh

Since Specialization
Citations

This map shows the geographic impact of Yongmoo Suh'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 Yongmoo Suh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yongmoo Suh more than expected).

Fields of papers citing papers by Yongmoo Suh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yongmoo Suh. 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 Yongmoo Suh. The network helps show where Yongmoo Suh may publish in the future.

Co-authorship network of co-authors of Yongmoo Suh

This figure shows the co-authorship network connecting the top 25 collaborators of Yongmoo Suh. A scholar is included among the top collaborators of Yongmoo Suh 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 Yongmoo Suh. Yongmoo Suh 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.
Suh, Yongmoo, et al.. (2020). Impact of Corporate Personality on the Relationship between Job Satisfaction and Turnover Rate :Based on the Corporate Review of Job-Planet. Journal of the Korea society of IT services. 19(3). 35–56.
2.
Suh, Yongmoo, et al.. (2020). Identifying financial statement fraud with decision rules obtained from Modified Random Forest. Data Technologies and Applications. 54(2). 235–255. 32 indexed citations
3.
Suh, Yongmoo, et al.. (2018). Quick-and-Wide Propagation of Disaster Tweets: Its Measurement and Implications. Journal of the Association for Information Systems. 1 indexed citations
4.
Choi, Keunho, Gun-Woo Kim, Yongmoo Suh, & Donghee Yoo. (2016). Assignment of collaborators to multiple business problems using genetic algorithm. Information Systems and e-Business Management. 15(4). 877–895. 1 indexed citations
5.
Choi, Keunho, Yongmoo Suh, & Donghee Yoo. (2016). Extended Collaborative Filtering Technique for Mitigating the Sparsity Problem. International Journal of Computers Communications & Control. 11(5). 631–631. 7 indexed citations
6.
Yoo, Donghee, Keunho Choi, Hanjun Lee, & Yongmoo Suh. (2015). An Ontology-based Co-creation Enhancing System for Idea Recommendation in an Online Community. ACM SIGMIS Database the DATABASE for Advances in Information Systems. 46(3). 9–22. 5 indexed citations
7.
Lee, Hanjun & Yongmoo Suh. (2014). Social media comparative analysis based on multidimensional scaling. Journal of the Korean Data and Information Science Society. 25(3). 665–676. 1 indexed citations
8.
Lee, Hanjun, et al.. (2013). The More the Worse? Mining Valuable Ideas with Sentiment Analysis for Idea Recommendation. Pacific Asia Conference on Information Systems. 30. 5 indexed citations
9.
Choi, Keunho, et al.. (2013). Double Ensemble Approaches to Predicting Firms’ Credit Rating. Pacific Asia Conference on Information Systems. 158. 1 indexed citations
10.
Yoo, Donghee, Keunho Choi, Yongmoo Suh, & Gun-Woo Kim. (2013). Building and evaluating a collaboratively built structured folksonomy. Journal of Information Science. 39(5). 593–607. 6 indexed citations
11.
Choi, Keunho, Gun-Woo Kim, Donghee Yoo, & Yongmoo Suh. (2011). New Collaborative Filtering Based on Similarity Integration and Temporal Information. Journal of Intelligence and Information Systems. 17(3). 147–168. 3 indexed citations
12.
Yoo, Donghee, Gun-Woo Kim, Keunho Choi, & Yongmoo Suh. (2011). CTKOS : Categorized Tag-based Knowledge Organization System. Journal of Intelligence and Information Systems. 17(4). 59–74. 1 indexed citations
13.
Suh, Yongmoo, et al.. (2010). CRM Strategies for A Small-Sized Online Shopping Mall Based on Association Rules and Sequential Patterns. Journal of the Association for Information Systems. 3 indexed citations
14.
Choi, Keunho, et al.. (2010). Classification and Sequential Pattern Analysis for Improving Managerial Efficiency and Providing Better Medical Service in Public Healthcare Centers. Healthcare Informatics Research. 16(2). 67–67. 8 indexed citations
15.
Kim, Minyoung, Gun-Woo Kim, & Yongmoo Suh. (2009). Ontological Representation of Business Process Knowledge and Its Evolution Using Process Mining Techniques. 679–684.
16.
Suh, Yongmoo, et al.. (2009). Length-of-Stay Prediction Model of Appendicitis using Artificial Neural Networks and Decision Tree. Journal of the Korea Academia-Industrial cooperation Society. 10(6). 1424–1432. 1 indexed citations
17.
Yoo, Donghee, Gun-Woo Kim, & Yongmoo Suh. (2009). Hotel-Domain Ontology for a Semantic Hotel Search System. Information Technology & Tourism. 11(1). 67–84. 3 indexed citations
18.
Yoo, Donghee & Yongmoo Suh. (2008). An Ontology-based Hotel Search System Using Semantic Web Technologies. The e-Business Studies. 13(4). 71–92. 5 indexed citations
19.
Suh, Yongmoo, et al.. (2004). Comparison of Hospital Charge Prediction Models for Colorectal Cancer Patients: Neural Network vs. Decision Tree Models. Journal of Korean Medical Science. 19(5). 677–677. 33 indexed citations
20.
Suh, Yongmoo, et al.. (1993). An IBIS and object-oriented approach to scientific research data management. Journal of Systems and Software. 23(2). 183–197. 5 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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