Kyong-Ho Lee

2.8k total citations · 1 hit paper
142 papers, 2.1k citations indexed

About

Kyong-Ho Lee is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Kyong-Ho Lee has authored 142 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Information Systems, 67 papers in Artificial Intelligence and 52 papers in Computer Networks and Communications. Recurrent topics in Kyong-Ho Lee's work include Service-Oriented Architecture and Web Services (40 papers), Semantic Web and Ontologies (31 papers) and Topic Modeling (21 papers). Kyong-Ho Lee is often cited by papers focused on Service-Oriented Architecture and Web Services (40 papers), Semantic Web and Ontologies (31 papers) and Topic Modeling (21 papers). Kyong-Ho Lee collaborates with scholars based in South Korea, United States and China. Kyong-Ho Lee's co-authors include Naveen Verma, Xiongnan Jin, Chaoqun Hong, Jian Zhang, Jun Yu, Yeon‐Seok Kim, Byungkook Oh, Soon Hyung Hong, Eun‐Pyo Kim and Youngmoo E. Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Polymer.

In The Last Decade

Kyong-Ho Lee

126 papers receiving 2.0k citations

Hit Papers

Multimodal Face-Pose Estimation With Multitask Manifold D... 2018 2026 2020 2023 2018 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Multimodal Face-Pose Estimation With Multitask Manifold Deep Learning
    2018 268 citations Chaoqun Hong, Jun Yu et al. IEEE Transactions on Industrial Informatics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kyong-Ho Lee South Korea 24 616 604 471 453 259 142 2.1k
Han Cai China 22 1.0k 1.6× 436 0.7× 491 1.0× 832 1.8× 432 1.7× 79 2.5k
Yantao Li China 28 531 0.9× 350 0.6× 241 0.5× 712 1.6× 412 1.6× 149 2.6k
Wenjun Jiang China 25 877 1.4× 455 0.8× 492 1.0× 323 0.7× 1.3k 5.0× 78 2.9k
Joan Lu United Kingdom 20 333 0.5× 413 0.7× 422 0.9× 133 0.3× 143 0.6× 185 1.6k
Yongqiang Cheng China 24 410 0.7× 287 0.5× 308 0.7× 381 0.8× 371 1.4× 125 2.0k
Guoxin Wang China 27 523 0.8× 369 0.6× 87 0.2× 359 0.8× 292 1.1× 192 2.5k
G. Ramkumar India 29 407 0.7× 267 0.4× 409 0.9× 343 0.8× 535 2.1× 200 2.4k
Taeho Jung United States 25 777 1.3× 410 0.7× 183 0.4× 236 0.5× 634 2.4× 75 1.8k
Mitsuhiro Hirano Japan 11 327 0.5× 222 0.4× 213 0.5× 244 0.5× 668 2.6× 24 2.4k

Countries citing papers authored by Kyong-Ho Lee

Since Specialization
Citations

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

Fields of papers citing papers by Kyong-Ho Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyong-Ho Lee. 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 Kyong-Ho Lee. The network helps show where Kyong-Ho Lee may publish in the future.

Co-authorship network of co-authors of Kyong-Ho Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Kyong-Ho Lee. A scholar is included among the top collaborators of Kyong-Ho Lee 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 Kyong-Ho Lee. Kyong-Ho Lee 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.
Kim, Donghyun, et al.. (2025). CoreSense: Social Commonsense Knowledge-Aware Context Refinement for Conversational Recommender System. IEEE Transactions on Knowledge and Data Engineering. 37(4). 1702–1713.
2.
Lee, Kyong-Ho, et al.. (2025). Active Learning Framework for Improving Knowledge Graph Accuracy. IEEE Access. 13. 47500–47513. 1 indexed citations
3.
Oh, Byungkook, et al.. (2024). Embedding Two-View Knowledge Graphs with Class Inheritance and Structural Similarity. 3931–3941. 1 indexed citations
4.
Lee, Kyong-Ho, et al.. (2024). OmEGa(Ω): Ontology-based information extraction framework for constructing task-centric knowledge graph from manufacturing documents with large language model. Advanced Engineering Informatics. 64. 103001–103001. 4 indexed citations
5.
Kim, Taeyoung, et al.. (2024). Bottom-up propagation of hierarchical dependency for multi-behavior recommendation. Engineering Applications of Artificial Intelligence. 138. 109364–109364.
6.
Lee, Kyong-Ho, et al.. (2024). Multi-domain dialogue state tracking via dual dynamic graph with hierarchical slot selector. Knowledge-Based Systems. 308. 112754–112754.
7.
Oh, Byungkook, et al.. (2023). Active learning for cross-sentence n-ary relation extraction. Information Sciences. 645. 119328–119328. 1 indexed citations
8.
Lee, Kyong-Ho, et al.. (2023). Confident Action Decision via Hierarchical Policy Learning for Conversational Recommendation. 1386–1395. 4 indexed citations
9.
Oh, Byungkook, et al.. (2021). Active Learning for Knowledge Graph Schema Expansion. IEEE Transactions on Knowledge and Data Engineering. 34(12). 5610–5620. 5 indexed citations
10.
Jin, Xiongnan, et al.. (2021). DORIC: discovering topological relations based on spatial link composition. Knowledge and Information Systems. 63(10). 2645–2669.
11.
Lee, Kyong-Ho, et al.. (2020). Processing knowledge graph-based complex questions through question decomposition and recomposition. Information Sciences. 523. 234–244. 17 indexed citations
12.
Lee, Kyong-Ho, et al.. (2019). Proactive Policy for Efficiently Updating Join Views on Continuous Queries Over Data Streams and Linked Data. IEEE Access. 7. 86226–86241. 1 indexed citations
13.
Hong, Chaoqun, Jun Yu, Jian Zhang, Xiongnan Jin, & Kyong-Ho Lee. (2018). Multimodal Face-Pose Estimation With Multitask Manifold Deep Learning. IEEE Transactions on Industrial Informatics. 15(7). 3952–3961. 268 indexed citations breakdown →
14.
Jin, Xiongnan, et al.. (2018). Quantitative Computation of Social Strength in Social Internet of Things. IEEE Internet of Things Journal. 5(5). 4066–4075. 18 indexed citations
15.
Jin, Xiongnan, et al.. (2018). Collective Keyword Query on a Spatial Knowledge Base. IEEE Transactions on Knowledge and Data Engineering. 31(11). 2051–2062. 9 indexed citations
16.
Jin, Xiongnan, et al.. (2016). Proactive Replication of Dynamic Linked Data for Scalable RDF Stream Processing.. International Semantic Web Conference. 1690. 2 indexed citations
17.
Lee, Kyong-Ho, et al.. (2013). RDFChain: Chain centric storage for scalable join processing of RDF graphs using mapreduce and HBase. International Semantic Web Conference. 1035. 249–252. 11 indexed citations
18.
Kim, Yeon‐Seok, et al.. (2011). A Cluster-Based Web Service Discovery in MANET Environments. SHILAP Revista de lepidopterología. 8 indexed citations
19.
Lee, Kyong-Ho. (2011). Implementation of Serious Game Environment to Reflect Exercise using Human Power Generation System. 175–178.
20.
Lee, Kyong-Ho, et al.. (2005). Clustering of XML Schemas for Information Integration. Journal of Computer Information Systems. 46(2). 3–13. 2 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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