Aaron Eberhart
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Semantic Web and Ontologies
- Explainable Artificial Intelligence (XAI)
- Advanced Graph Neural Networks
- Neural Networks and Applications
- Natural Language Processing Techniques
- Machine Learning in Healthcare
Papers in
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- Semantic Web and Ontologies 6
- Neural Networks and Applications 4
- Topic Modeling 4
- Advanced Graph Neural Networks 3
- Explainable Artificial Intelligence (XAI) 2
- Natural Language Processing Techniques 2
- Cognitive Science and Mapping 1
-
- Service-Oriented Architecture and Web Services 2
- Co-authors
- Pascal Hitzler (9 shared papers)Md Kamruzzaman Sarker (4 shared papers)Lu Zhou (2 shared papers)Monireh Ebrahimi (4 shared papers)Federico Bianchi (2 shared papers)Cogan Shimizu (4 shared papers)Adam C. Kellerman (1 shared paper)Christopher A. Stevens (1 shared paper)
- Journals
- National Science Review (1 paper)Applied Intelligence (1 paper)Lecture notes in computer science (2 papers)AI Communications (1 paper)Communications in computer and information science (2 papers)
- Partner nations
- United StatesItalyIndonesia
In The Last Decade
Aaron Eberhart
13 papers receiving 219 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 149
- Health Informatics 4
- Computer Vision and Pattern Recognition 25
- Computational Theory and Mathematics 15
- Information Systems 17
Countries citing papers authored by Aaron Eberhart
This map shows the geographic impact of Aaron Eberhart'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 Aaron Eberhart with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aaron Eberhart more than expected).
Fields of papers citing papers by Aaron Eberhart
This network shows the impact of papers produced by Aaron Eberhart. 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 Aaron Eberhart. The network helps show where Aaron Eberhart may publish in the future.
Co-authors
The 17 scholars most cited alongside Aaron Eberhart, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 104 | |
| 2 | 2022 | 82 | |
| 3 | 2021 | 24 | |
| 4 | Neuro-Symbolic Deductive Reasoning for Cross-Knowledge Graph Entailment. | 2021 | 3 |
| 5 | 2020 | 3 | |
| 6 | 2021 | 3 | |
| 7 | 2021 | 3 | |
| 8 | 2024 | 2 | |
| 9 | 2021 | 2 | |
| 10 | 2019 | 1 | |
| 11 | 2023 | 1 | |
| 12 | 2018 | 1 | |
| 13 | 2024 | 1 |
About Aaron Eberhart
Aaron Eberhart is a scholar working on Artificial Intelligence, Information Systems, Management Information Systems, Astronomy and Astrophysics and Computational Theory and Mathematics, having authored 13 papers that have together received 230 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (6 papers), Neural Networks and Applications (4 papers), Topic Modeling (4 papers), Advanced Graph Neural Networks (3 papers), Explainable Artificial Intelligence (XAI) (2 papers), Natural Language Processing Techniques (2 papers), Service-Oriented Architecture and Web Services (2 papers) and Cognitive Science and Mapping (1 paper). The work is most often cited by research in Artificial Intelligence (149 citations), Health Informatics (4 citations), Computer Vision and Pattern Recognition (25 citations), Computational Theory and Mathematics (15 citations) and Information Systems (17 citations). Aaron Eberhart has collaborated with scholars based in United States, Italy and Indonesia. Frequent co-authors include Pascal Hitzler, Md Kamruzzaman Sarker, Lu Zhou, Monireh Ebrahimi, Federico Bianchi, Cogan Shimizu, Adam C. Kellerman, Christopher A. Stevens, Christopher W. Myers and Peter N. Haase. Their work appears in journals such as National Science Review, Applied Intelligence, Lecture notes in computer science, AI Communications and Communications in computer and information science.
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.