Jinoh Oh

1.6k citations
30 papers · 1.1k indexed · 1 hit paper · h-index 14
Topics
Recommender Systems and Techniques (12 papers)Advanced Graph Neural Networks (7 papers)Topic Modeling (5 papers)

In The Last Decade

Jinoh Oh

30 papers receiving 1.1k citations

Hit Papers

Convolutional Matrix Factorization for Document Context-A...20162026201920222016100200300400500

Peers

Jinoh Oh
Comparison fields: 5 of 66
  • Information Systems 812
  • Artificial Intelligence 662
  • Computer Vision and Pattern Recognition 324
  • Computer Networks and Communications 153
  • Sociology and Political Science 137
Replace István Pilászy with:
István Pilászy Hungary
Dimitrios Rafailidis Greece
Leandro Balby Marinho Brazil
Dhruv Gupta Germany
Roberto Turrin Italy
Nathan N. Liu Hong Kong
Xiwang Yang China
Qinyong Wang China
Lucas Drumond Germany
Jinoh Oh relative to István Pilászy Hungary István Pilászy's profile →
Citations per field
00.5×3.7×
István Pilászy · 1×
Citations per year

Countries citing papers authored by Jinoh Oh

Since Specialization
Citations

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

Fields of papers citing papers by Jinoh Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinoh Oh

This figure shows the co-authorship network connecting the top 25 collaborators of Jinoh Oh. A scholar is included among the top collaborators of Jinoh Oh 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 Jinoh Oh. Jinoh Oh 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
#WorkIndexed citations
1 5
2 5
3 3
4 3
5 3
6 31
7 26
8 31
9 18
10
Convolutional Matrix Factorization for Document Context-Aware Recommendationbreakdown →
521
11 7
12 12
13 30
14 29
15 11
16 2
17 60
18 89
19 21
20 7

About Jinoh Oh

Jinoh Oh is a scholar working on Computational Mathematics, Information Systems and Artificial Intelligence, having authored 30 papers that have together received 1.1k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (12 papers), Advanced Graph Neural Networks (7 papers) and Topic Modeling (5 papers). The work is most often cited by research in Computational Mathematics (41 citations), Information Systems (812 citations) and Artificial Intelligence (662 citations). Jinoh Oh has collaborated with scholars based in South Korea, United States and Qatar. Frequent co-authors include Hwanjo Yu, Yejin Kim, Chanyoung Park, Sungyoung Lee, Chanyoung Park, Hwanjo Yu, Jong Kim, Wook-Shin Han, Sungchul Kim and Min Song. Their work appears in journals such as BMC Bioinformatics, Information Sciences and Knowledge-Based Systems.

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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