Go Eun Heo
Impact in
- General Social Sciences top 5%
- Computational and Text Analysis Methods
-
- scientometrics and bibliometrics research
Papers in
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- Biomedical Text Mining and Ontologies 15
- Bioinformatics and Genomic Networks 2
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- Advanced Text Analysis Techniques 6
- Semantic Web and Ontologies 6
- Topic Modeling 5
- Natural Language Processing Techniques 2
- Co-authors
- Min Song (21 shared papers)Da-Hee Lee (2 shared papers)Won Chul Kim (1 shared paper)Su Yeon Kim (1 shared paper)Jeong‐Hoon Lee (3 shared papers)Chaomei Chen (1 shared paper)Yoo Kyung Jeong (2 shared papers)Ying Ding (1 shared paper)
- Journals
- Journal of Informetrics (4 papers)BMC Bioinformatics (3 papers)Scientometrics (2 papers)BMC Medical Informatics and Decision Making (2 papers)Journal of Biomedical Informatics (1 paper)
- Partner nations
- South KoreaAustraliaUnited States
In The Last Decade
Go Eun Heo
19 papers receiving 255 citations
Peers
Comparison fields: 5 of 76
- General Social Sciences 20
- Statistics, Probability and Uncertainty 25
- Artificial Intelligence 107
- Molecular Biology 117
- Information Systems 38
Countries citing papers authored by Go Eun Heo
This map shows the geographic impact of Go Eun Heo'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 Go Eun Heo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Go Eun Heo more than expected).
Fields of papers citing papers by Go Eun Heo
This network shows the impact of papers produced by Go Eun Heo. 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 Go Eun Heo. The network helps show where Go Eun Heo may publish in the future.
Co-authors
The 19 scholars most cited alongside Go Eun Heo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 81 | |
| 2 | 2014 | 35 | |
| 3 | 2018 | 26 | |
| 4 | 2014 | 23 | |
| 5 | 2017 | 22 | |
| 6 | 2016 | 13 | |
| 7 | 2013 | 13 | |
| 8 | 2015 | 13 | |
| 9 | 2016 | 9 | |
| 10 | 2022 | 8 | |
| 11 | 2020 | 8 | |
| 12 | 2019 | 7 | |
| 13 | 2014 | 6 | |
| 14 | 2019 | 6 | |
| 15 | 2013 | 4 | |
| 16 | 2019 | 1 | |
| 17 | 2014 | 1 | |
| 18 | 2015 | 1 | |
| 19 | 2015 | 1 | |
| 20 | 2015 | 0 |
About Go Eun Heo
Go Eun Heo is a scholar working on Molecular Biology, Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty, having authored 23 papers that have together received 278 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (15 papers), Advanced Text Analysis Techniques (6 papers), Semantic Web and Ontologies (6 papers), Topic Modeling (5 papers), Complex Network Analysis Techniques (3 papers), Bioinformatics and Genomic Networks (2 papers), Natural Language Processing Techniques (2 papers) and scientometrics and bibliometrics research (2 papers). The work is most often cited by research in General Social Sciences (20 citations), Statistics, Probability and Uncertainty (25 citations), Artificial Intelligence (107 citations), Molecular Biology (117 citations) and Information Systems (38 citations). Go Eun Heo has collaborated with scholars based in South Korea, Australia and United States. Frequent co-authors include Min Song, Da-Hee Lee, Won Chul Kim, Su Yeon Kim, Jeong‐Hoon Lee, Chaomei Chen, Yoo Kyung Jeong, Ying Ding, Qing Xie and Karin Verspoor. Their work appears in journals such as Journal of Informetrics, BMC Bioinformatics, Scientometrics, BMC Medical Informatics and Decision Making and Journal of Biomedical Informatics.
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.