Daniel Berleant

1.7k total citations
78 papers, 982 citations indexed

About

Daniel Berleant is a scholar working on Artificial Intelligence, Molecular Biology and Management Science and Operations Research. According to data from OpenAlex, Daniel Berleant has authored 78 papers receiving a total of 982 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 16 papers in Molecular Biology and 14 papers in Management Science and Operations Research. Recurrent topics in Daniel Berleant's work include Semantic Web and Ontologies (13 papers), Biomedical Text Mining and Ontologies (12 papers) and Probabilistic and Robust Engineering Design (8 papers). Daniel Berleant is often cited by papers focused on Semantic Web and Ontologies (13 papers), Biomedical Text Mining and Ontologies (12 papers) and Probabilistic and Robust Engineering Design (8 papers). Daniel Berleant collaborates with scholars based in United States, France and Austria. Daniel Berleant's co-authors include Benjamin Kuipers, Jianzhong Zhang, Eve Syrkin Wurtele, Jie Ding, Dan Nettleton, Chaim Goodman-Strauss, Hal Berghel, Jing Ding, Scott Ferson and Lizhi Xie and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and Communications of the ACM.

In The Last Decade

Daniel Berleant

70 papers receiving 898 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel Berleant United States 14 500 283 163 155 127 78 982
Fuyuan Xiao China 16 442 0.9× 28 0.1× 194 1.2× 60 0.4× 334 2.6× 53 1.0k
Daijun Wei China 15 131 0.3× 68 0.2× 95 0.6× 43 0.3× 161 1.3× 28 961
Christian Posse United States 17 255 0.5× 59 0.2× 40 0.2× 46 0.3× 66 0.5× 39 792
Hongming Mo China 15 186 0.4× 26 0.1× 91 0.6× 77 0.5× 318 2.5× 23 724
Omar Barukab Saudi Arabia 17 130 0.3× 190 0.7× 83 0.5× 17 0.1× 95 0.7× 53 730
Andrea G. B. Tettamanzi Italy 18 519 1.0× 58 0.2× 179 1.1× 9 0.1× 157 1.2× 87 893
Ad Feelders Netherlands 16 414 0.8× 53 0.2× 153 0.9× 19 0.1× 110 0.9× 66 770
Xin Tong United States 13 207 0.4× 61 0.2× 18 0.1× 88 0.6× 69 0.5× 46 576
Meizhu Li China 11 129 0.3× 50 0.2× 73 0.4× 32 0.2× 125 1.0× 28 465

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-authorship network of co-authors of Daniel Berleant

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Berleant. A scholar is included among the top collaborators of Daniel Berleant 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 Daniel Berleant. Daniel Berleant 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
1.
Segall, Richard S., et al.. (2024). A Customer Service Chatbot Using Python, Machine Learning, and Artificial Intelligence. 148–156. 1 indexed citations
2.
Berleant, Daniel, et al.. (2023). Using Discrete-Event Simulation to Balance Staff Allocation and Patient Flow between Clinic and Surgery. SHILAP Revista de lepidopterología. 4(4). 567–584. 2 indexed citations
3.
Dai, Wei & Daniel Berleant. (2022). Discovering Limitations of Image Quality Assessments with Noised Deep Learning Image Sets. 2022 IEEE International Conference on Big Data (Big Data). 10. 3735–3744. 1 indexed citations
4.
Segall, Richard S., et al.. (2021). Forecasting of a Technology Using Quantitative Satellite Lifetime Data. SHILAP Revista de lepidopterología.
5.
Zhang, Lifeng, Daniel Berleant, Jing Ding, & Eve Syrkin Wurtele. (2013). Automatic extraction of biomolecular interactions: an empirical approach. BMC Bioinformatics. 14(1). 234–234. 2 indexed citations
6.
Berleant, Daniel, et al.. (2011). World oil reserves data: information quality assessment analysis.. ICIQ. 1 indexed citations
7.
Wren, Jonathan D., Doris M. Kupfer, Edward J. Perkins, Susan M. Bridges, & Daniel Berleant. (2010). Proceedings of the 2010 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinformatics. 11(S6). S1–S1. 1 indexed citations
8.
Zhang, Lifeng, et al.. (2009). PathBinder – text empirics and automatic extraction of biomolecular interactions. BMC Bioinformatics. 10(S11). S18–S18. 7 indexed citations
9.
Berleant, Daniel, et al.. (2007). Portfolio management under epistemic uncertainty using stochastic dominance and information-gap theory. International Journal of Approximate Reasoning. 49(1). 101–116. 11 indexed citations
10.
Berleant, Daniel, Martine Ceberio, Gang Xiang, & Владик Крейнович. (2007). Towards adding probabilities and correlations to interval computations. International Journal of Approximate Reasoning. 46(3). 499–510. 4 indexed citations
11.
Ding, Jing, Daniel Berleant, Eve Syrkin Wurtele, et al.. (2005). Using the biological taxonomy to access biological literature with PathBinderH. Computer applications in the biosciences. 21(10). 2560–2562. 13 indexed citations
12.
Berleant, Daniel, et al.. (2005). Electric Company Portfolio Optimization Under Interval Stochastic Dominance Constraints.. 51–57. 8 indexed citations
13.
Zhang, Jianzhong & Daniel Berleant. (2005). Arithmetic on Random Variables: Squeezing the Envelopes with New Joint Distribution Constraints. 416–422. 7 indexed citations
14.
Berleant, Daniel, et al.. (2004). Information gap decision theory as a tool for strategic bidding in competitive electricity markets. 421–426. 17 indexed citations
15.
Regan, Helen M., Scott Ferson, & Daniel Berleant. (2003). Equivalence of methods for uncertainty propagation of real-valued random variables. International Journal of Approximate Reasoning. 36(1). 1–30. 49 indexed citations
16.
Berleant, Daniel, et al.. (1998). Version Augmented URIs for Reference Permanence via an Apache Module Design.. Computer Networks. 30. 337–345. 3 indexed citations
17.
Berleant, Daniel & Benjamin Kuipers. (1997). Qualitative and quantitative simulation: bridging the gap. Artificial Intelligence. 95(2). 215–255. 83 indexed citations
18.
Doyle, Richard J., et al.. (1993). Sensor selection in complex system monitoring using information quantification and causal reasoning. MIT Press eBooks. 229–244. 1 indexed citations
19.
Berleant, Daniel & Benjamin Kuipers. (1993). Qualitative-numeric simulation with Q3. MIT Press eBooks. 3–16. 15 indexed citations
20.
Kuipers, Benjamin & Daniel Berleant. (1988). Using incomplete quantitative knowledge in qualitative reasoning. National Conference on Artificial Intelligence. 5(6). 324–329. 105 indexed citations

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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