Daniel Berleant

1.7k citations
80 papers · 994 · h-index 14

Impact in

Papers in

Daniel Berleant

70 papers receiving 908 citations

Peers

Daniel Berleant
Comparison fields: 5 of 116
  • Statistics, Probability and Uncertainty 159
  • Artificial Intelligence 452
  • Management Science and Operations Research 133
  • Computational Theory and Mathematics 161
  • Software 33
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Berleant

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Daniel Berleant Line = papers co-authored together Daniel Berleant links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001175
2
Using incomplete quantitative knowledge in qualitative reasoning
1988105
3 199783
4 199859
5 200350
6 200348
7 200439
8 202235
9 200431
10 201225
11 200422
12 199919
13
Information gap decision theory as a tool for strategic bidding in competitive electricity markets
200417
14
Qualitative-numeric simulation with Q3
199315
15 200513
16 200512
17 200912
18 199511
19 200711
20 202310

About Daniel Berleant

Daniel Berleant is a scholar working on Artificial Intelligence, Molecular Biology, Management Science and Operations Research, Information Systems and Statistics, Probability and Uncertainty, having authored 80 papers that have together received 994 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (12 papers), Semantic Web and Ontologies (11 papers), Probabilistic and Robust Engineering Design (8 papers), Numerical Methods and Algorithms (7 papers), AI-based Problem Solving and Planning (6 papers), Fault Detection and Control Systems (5 papers), Data Quality and Management (4 papers) and Natural Language Processing Techniques (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (159 citations), Artificial Intelligence (452 citations), Management Science and Operations Research (133 citations), Computational Theory and Mathematics (161 citations) and Software (33 citations). Daniel Berleant has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Benjamin Kuipers, Jianzhong Zhang, Eve Syrkin Wurtele, Jie Ding, Dan Nettleton, Chaim Goodman-Strauss, Hal Berghel, Scott Ferson, Helen M. Regan and Jing Ding. Their work appears in journals such as BMC Bioinformatics, Computer, International Journal of Approximate Reasoning, Bioinformatics and Communications of the ACM.

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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