Daniel Berleant
Impact in
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- Probabilistic and Robust Engineering Design
- Artificial Intelligence top 5%
- AI-based Problem Solving and Planning
- Semantic Web and Ontologies
- Topic Modeling
- Natural Language Processing Techniques
Papers in
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- Semantic Web and Ontologies 11
- AI-based Problem Solving and Planning 7
- Bayesian Modeling and Causal Inference 5
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- Data Quality and Management 5
- Co-authors
- Benjamin J. Kuipers (4 shared papers)Jianzhong Zhang (5 shared papers)Eve Syrkin Wurtele (10 shared papers)Jie Ding (1 shared paper)Dan S. Nettleton (1 shared paper)Chaim Goodman-Strauss (2 shared papers)Hal Berghel (4 shared papers)Scott Ferson (2 shared papers)
- Journals
- BMC Bioinformatics (4 papers)Computer (3 papers)International Journal of Approximate Reasoning (3 papers)Bioinformatics (2 papers)Artificial Intelligence (1 paper)
- Partner nations
- United StatesFranceAustria
In The Last Decade
Daniel Berleant
86 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 123
- Statistics, Probability and Uncertainty 203
- Artificial Intelligence 540
- Management Science and Operations Research 165
- Computational Theory and Mathematics 216
- Statistics and Probability 79
Countries citing papers authored by Daniel Berleant
This map shows the geographic impact of Daniel Berleant'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 Daniel Berleant with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Berleant more than expected).
Fields of papers citing papers by Daniel Berleant
This network shows the impact of papers produced by Daniel Berleant. 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 Daniel Berleant. The network helps show where Daniel Berleant may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Berleant, 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 91 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 193 | |
| 2 | Using incomplete quantitative knowledge in qualitative reasoning | 1988 | 118 |
| 3 | 1997 | 91 | |
| 4 | 1998 | 68 | |
| 5 | 2003 | 57 | |
| 6 | 2003 | 55 | |
| 7 | 2004 | 47 | |
| 8 | 2022 | 39 | |
| 9 | 2004 | 38 | |
| 10 | 2012 | 29 | |
| 11 | 1996 | 29 | |
| 12 | 2004 | 24 | |
| 13 | 2023 | 20 | |
| 14 | 1999 | 20 | |
| 15 | Qualitative-numeric simulation with Q3 | 1993 | 17 |
| 16 | Information gap decision theory as a tool for strategic bidding in competitive electricity markets | 2004 | 17 |
| 17 | 1998 | 16 | |
| 18 | 2005 | 14 | |
| 19 | 1995 | 13 | |
| 20 | 2003 | 13 |
About Daniel Berleant
Daniel Berleant is a scholar working on Artificial Intelligence, Management Science and Operations Research, Statistics, Probability and Uncertainty, Computational Theory and Mathematics and Information Systems, having authored 91 papers that have together received 1.2k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (14 papers), Semantic Web and Ontologies (11 papers), Numerical Methods and Algorithms (9 papers), Probabilistic and Robust Engineering Design (8 papers), AI-based Problem Solving and Planning (7 papers), Bioinformatics and Genomic Networks (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Data Quality and Management (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (203 citations), Artificial Intelligence (540 citations), Management Science and Operations Research (165 citations), Computational Theory and Mathematics (216 citations) and Statistics and Probability (79 citations). Daniel Berleant has collaborated with scholars based in United States, France and Austria. Frequent co-authors include Benjamin J. Kuipers, Jianzhong Zhang, Eve Syrkin Wurtele, Jie Ding, Dan S. Nettleton, Chaim Goodman-Strauss, Hal Berghel, Scott Ferson, Jing Ding and Lizhi Xie. Their work appears in journals such as BMC Bioinformatics, Computer, International Journal of Approximate Reasoning, Bioinformatics and Artificial Intelligence.
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.