Doo-Soon Park

1.0k total citations
70 papers, 656 citations indexed

About

Doo-Soon Park is a scholar working on Information Systems, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Doo-Soon Park has authored 70 papers receiving a total of 656 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Information Systems, 21 papers in Computer Networks and Communications and 19 papers in Artificial Intelligence. Recurrent topics in Doo-Soon Park's work include Rough Sets and Fuzzy Logic (13 papers), Complex Network Analysis Techniques (13 papers) and Recommender Systems and Techniques (8 papers). Doo-Soon Park is often cited by papers focused on Rough Sets and Fuzzy Logic (13 papers), Complex Network Analysis Techniques (13 papers) and Recommender Systems and Techniques (8 papers). Doo-Soon Park collaborates with scholars based in South Korea, China and United Kingdom. Doo-Soon Park's co-authors include Fei Hao, Young‐Sik Jeong, Zheng Pei, Geyong Min, Laurence T. Yang, HwaMin Lee�, Youn‐Hee Han, Yonghwan Kim, Namje Park and Han‐Chieh Chao and has published in prestigious journals such as IEEE Access, IEEE Journal on Selected Areas in Communications and Sustainability.

In The Last Decade

Doo-Soon Park

67 papers receiving 624 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Doo-Soon Park South Korea 15 238 195 186 119 98 70 656
William Eberle United States 14 280 1.2× 185 0.9× 470 2.5× 44 0.4× 106 1.1× 57 841
Feng Pan China 15 203 0.9× 152 0.8× 482 2.6× 74 0.6× 121 1.2× 62 765
Rosa Meo Italy 13 181 0.8× 340 1.7× 322 1.7× 156 1.3× 89 0.9× 51 717
Patricia Riddle New Zealand 12 99 0.4× 174 0.9× 430 2.3× 55 0.5× 91 0.9× 57 692
Weiyi Liu China 13 111 0.5× 96 0.5× 275 1.5× 61 0.5× 98 1.0× 66 550
Rana Forsati Iran 19 193 0.8× 430 2.2× 647 3.5× 85 0.7× 202 2.1× 39 1.1k
Yun Sing Koh New Zealand 17 145 0.6× 395 2.0× 636 3.4× 145 1.2× 78 0.8× 81 986
Mark Nicholson United Kingdom 10 103 0.4× 92 0.5× 207 1.1× 85 0.7× 61 0.6× 31 688
Ahmet Zengi̇n Türkiye 13 202 0.8× 167 0.9× 334 1.8× 114 1.0× 497 5.1× 58 923

Countries citing papers authored by Doo-Soon Park

Since Specialization
Citations

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

Fields of papers citing papers by Doo-Soon Park

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Doo-Soon Park. 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 Doo-Soon Park. The network helps show where Doo-Soon Park may publish in the future.

Co-authorship network of co-authors of Doo-Soon Park

This figure shows the co-authorship network connecting the top 25 collaborators of Doo-Soon Park. A scholar is included among the top collaborators of Doo-Soon Park 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 Doo-Soon Park. Doo-Soon Park 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, Dae-Young, et al.. (2025). Integration of Federated Learning and Graph Convolutional Networks for Movie Recommendation Systems. Computers, materials & continua/Computers, materials & continua (Print). 83(2). 2041–2057.
2.
Park, Doo-Soon, et al.. (2024). Enhancing Sequence Movie Recommendation System Using Deep Learning and KMeans. Applied Sciences. 14(6). 2505–2505. 15 indexed citations
3.
Kim, Dae Young, et al.. (2024). Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems. Applied Sciences. 14(3). 1155–1155. 13 indexed citations
4.
Hao, Fei, et al.. (2023). BT-CKBQA: An efficient approach for Chinese knowledge base question answering. Data & Knowledge Engineering. 147. 102204–102204. 1 indexed citations
5.
Kim, Seokhoon, et al.. (2023). Detecting susceptible communities and individuals in hospital contact networks: a model based on social network analysis. Connection Science. 35(1). 2 indexed citations
6.
Park, Doo-Soon, et al.. (2020). Movie Recommendation System Based on Users’ Personal Information and Movies Rated Using the Method of k-Clique and Normalized Discounted Cumulative Gain. Journal of Information Processing Systems. 16(2). 494–507. 6 indexed citations
7.
Park, Doo-Soon, et al.. (2020). The Efficiency of a DoParallel Algorithm and an FCA Network Graph Applied to Recommendation System. Applied Sciences. 10(8). 2939–2939. 4 indexed citations
8.
Park, Doo-Soon, et al.. (2019). Movie Recommendation Algorithm Using Social Network Analysis to Alleviate Cold-Start Problem.. Journal of Information Processing Systems. 15(3). 616–631. 4 indexed citations
9.
Park, Doo-Soon, et al.. (2019). Personalized Movie Recommendation System Combining Data Mining with the k-Clique Method. Journal of Information Processing Systems. 15(5). 1141–1155. 9 indexed citations
10.
Min, Se Dong, Changwon Wang, Doo-Soon Park, & Jong Hyuk Park. (2018). Development of A Textile Capacitive Proximity Sensor and Gait Monitoring System for Smart Healthcare. Journal of Medical Systems. 42(4). 76–76. 15 indexed citations
11.
Park, Doo-Soon, Han‐Chieh Chao, Young‐Sik Jeong, & Namje Park. (2016). Advances in Computer Science and Ubiquitous Computing: CSA & CUTE. Springer eBooks. 19 indexed citations
12.
Kim, Mihui, et al.. (2015). Teaching-Learning Activity Modeling Based on Data Analysis. Symmetry. 7(1). 206–219. 7 indexed citations
13.
Park, Doo-Soon. (2013). Fault Tolerance and Energy Consumption Scheme of a Wireless Sensor Network. International Journal of Distributed Sensor Networks. 9(11). 396850–396850. 13 indexed citations
14.
Park, Doo-Soon. (2013). Improved Movie Recommendation System based-on Personal Propensity and Collaborative Filtering. 2(11). 475–482. 5 indexed citations
15.
16.
Park, Doo-Soon, et al.. (2008). Development of Contents to Improve the Web Accessibility for People with Visual Impairments. The Journal of Korean Association of Computer Education. 11(2). 45–53. 1 indexed citations
17.
Park, Doo-Soon & Min‐Hyung Choi. (2006). Interprocedural Transformations for Parallel Computing. Journal of Korea Multimedia Society. 9(12). 1700–1708. 2 indexed citations
18.
Park, Doo-Soon, et al.. (2006). THE DEVELOPMENT OF A GOODS RECOMMENDATION SYSTEM BASED ON WEB PERSONALIZATION. 232–235. 1 indexed citations
19.
Park, Doo-Soon, et al.. (2006). Construction Project-Based Material for Learning Visual Basic Using Flash and Photoshop. Journal of Korea Multimedia Society. 9(3). 353–359. 1 indexed citations
20.
Lee, Hyejung, Won‐Hwan Park, & Doo-Soon Park. (2003). An efficient algorithm for mining quantitative association rules to raise reliance of data in large databases. 672–681. 1 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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2026