Hong‐Gee Kim

3.1k total citations
151 papers, 1.8k citations indexed

About

Hong‐Gee Kim is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Hong‐Gee Kim has authored 151 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 39 papers in Molecular Biology and 37 papers in Information Systems. Recurrent topics in Hong‐Gee Kim's work include Semantic Web and Ontologies (33 papers), Biomedical Text Mining and Ontologies (17 papers) and Service-Oriented Architecture and Web Services (12 papers). Hong‐Gee Kim is often cited by papers focused on Semantic Web and Ontologies (33 papers), Biomedical Text Mining and Ontologies (17 papers) and Service-Oriented Architecture and Web Services (12 papers). Hong‐Gee Kim collaborates with scholars based in South Korea, United States and China. Hong‐Gee Kim's co-authors include Bo‐Yeong Kang, Youn‐Jung Son, Soo‐Kyoung Lee, Hai-Tao Zheng, Eunghee Kim, Sungin Lee, John G. Breslin, Seung‐Hak Baek, Hong Zheng and In‐Hwan Oh and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Hong‐Gee Kim

141 papers receiving 1.7k citations

Peers

Hong‐Gee Kim
Roy Schwartz United States
Zeeshan Ahmed United States
Shen Li China
Christoph M. Friedrich Germany
Sanjiv Jain India
Shanay Rab India
Yaqi Wang China
Hee‐Cheol Kim South Korea
Saman Zeeshan United States
Vincenzo Giordano Brazil
Roy Schwartz United States
Hong‐Gee Kim
Citations per year, relative to Hong‐Gee Kim Hong‐Gee Kim (= 1×) peers Roy Schwartz

Countries citing papers authored by Hong‐Gee Kim

Since Specialization
Citations

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

Fields of papers citing papers by Hong‐Gee Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hong‐Gee Kim. 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 Hong‐Gee Kim. The network helps show where Hong‐Gee Kim may publish in the future.

Co-authorship network of co-authors of Hong‐Gee Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Hong‐Gee Kim. A scholar is included among the top collaborators of Hong‐Gee Kim 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 Hong‐Gee Kim. Hong‐Gee Kim 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.
Zheng, Hai-Tao, et al.. (2025). Dual Denoising Diffusion Model for Session-based Social Recommendation. 1989–1999.
2.
Kim, Hong‐Gee, et al.. (2024). Multi-label classification with XGBoost for metabolic pathway prediction. BMC Bioinformatics. 25(1). 52–52. 7 indexed citations
3.
Zheng, Hai-Tao, et al.. (2024). A Segment Augmentation and Prediction Consistency Framework for Multi-label Unknown Intent Detection. ACM Transactions on Knowledge Discovery from Data. 18(9). 1–18. 1 indexed citations
4.
Fujita, Masashi, Kirsten Kübler, Paz Polak, et al.. (2022). COOBoostR: An Extreme Gradient Boosting-Based Tool for Robust Tissue or Cell-of-Origin Prediction of Tumors. Life. 13(1). 71–71. 2 indexed citations
5.
Hwang, Young Hoon, et al.. (2021). Deep Learning Ensemble Method for Classifying Glaucoma Stages Using Fundus Photographs and Convolutional Neural Networks. Current Eye Research. 46(10). 1516–1524. 32 indexed citations
6.
Lee, Ji-Min, Hong‐Gee Kim, Hong‐Keun Hyun, et al.. (2020). Analysis of brain connectivity during nitrous oxide sedation using graph theory. Scientific Reports. 10(1). 2354–2354. 14 indexed citations
7.
Kim, Hong‐Gee, et al.. (2019). A Study on Safety Analysis of Stationary LPG - Mobile Hydrogen Complex Refueling Station. 28(4). 48–60. 3 indexed citations
8.
Kim, Donghwan, et al.. (2019). Analysis of Operation Data Monitoring for LPG-Hydrogen Multi-Fueling Station. 28(4). 1–7. 2 indexed citations
9.
Zong, Nansu, et al.. (2017). xStore : Federated temporal query processing for large scale RDF triples on a cloud environment. Neurocomputing. 256. 5–12. 3 indexed citations
10.
Kim, Hong‐Gee, et al.. (2011). Using folksonomies for building user interest profile. 438–441. 4 indexed citations
11.
Scerri, Simon, et al.. (2011). Integrating Tagging into the Web of Data: Overview and Combination of Existing Tag Ontologies. 網際網路技術學刊. 12(4). 561–571. 6 indexed citations
12.
Zheng, Hai-Tao, Bo‐Yeong Kang, & Hong‐Gee Kim. (2008). Learnable focused crawling based on ontology. 264–275. 7 indexed citations
13.
Scerri, Simon, et al.. (2008). The State of the Art in Tag Ontologies: A Semantic Model for Tagging and Folksonomies. International Conference on Dublin Core and Metadata Applications. 128–137. 29 indexed citations
14.
Breslin, John G., et al.. (2008). int.ere.st: Building a Tag Sharing Service with the SCOT Ontology.. National Conference on Artificial Intelligence. 42–47. 7 indexed citations
15.
Breslin, John G., et al.. (2007). Tag mediated society with SCOT Ontology. International Semantic Web Conference. 105–112. 10 indexed citations
16.
Kim, Hong‐Gee, et al.. (2007). A Framework for Facilitating the Use of Formal Languages based on RDF. 대한산업공학회 춘계공동학술대회 논문집. 652–657.
17.
Kim, Hong‐Gee, et al.. (2007). Personal Electronic Document Retrieval System Using Semantic Web/Ontology Technologies. The e-Business Studies. 12(1). 135–149. 2 indexed citations
18.
Kim, Hong‐Gee, et al.. (2007). Tooth Positional Ontology Represented in OWL. 2288. 2 indexed citations
19.
Choi, Heechul, et al.. (2005). Development of a Formal Concept Analysis Tool for Scaling of Many-valued Context. 251–254. 1 indexed citations
20.
Kim, Hong‐Gee, et al.. (2004). Object Classification Using Pre-assigned Intervals in Image Databases.. 49–55.

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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