Richard E. Neapolitan

2.9k citations
56 papers · 1.6k · h-index 18

Impact in

Papers in

Richard E. Neapolitan

53 papers receiving 1.4k citations

Peers

Richard E. Neapolitan
Comparison fields: 5 of 152
  • Artificial Intelligence 725
  • Management Science and Operations Research 172
  • Software 37
  • Signal Processing 99
  • General Decision Sciences 16
Replace Stig Kjær Andersen with:
Stig Kjær Andersen Denmark
Antoni Ligęza Poland
Yun Xiong China
Lev V. Utkin Russia
Vicente García Mexico
José A. Gámez Spain
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Chris Drummond Canada
H. Altay Güvenir Türkiye
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Richard E. Neapolitan relative to Stig Kjær Andersen Denmark Stig Kjær Andersen's profile →
Citations per field
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Citations per year

Countries citing papers authored by Richard E. Neapolitan

Since Specialization
Citations

This map shows the geographic impact of Richard E. Neapolitan'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 Richard E. Neapolitan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard E. Neapolitan more than expected).

Fields of papers citing papers by Richard E. Neapolitan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard E. Neapolitan. 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 Richard E. Neapolitan. The network helps show where Richard E. Neapolitan may publish in the future.

Co-authors

The 25 scholars most cited alongside Richard E. Neapolitan, 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 Richard E. Neapolitan Line = papers co-authored together Richard E. Neapolitan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992368
2
Probabilistic reasoning in expert systems
1990259
3 200784
4 201876
5
Foundations of Algorithms
199675
6 201174
7 201856
8
Foundations of Algorithms Using C++ Pseudocode
200345
9
Data Mining: Know It All
200842
10 201837
11 201933
12 201631
13 201528
14 200925
15 201224
16
Utilizing Multidimensional Computer Adaptive Testing to Mitigate Burden With Patient Reported Outcomes.
201722
17
A fast algorithm for learning epistatic genomic relationships.
201020
18
Foundations Of Algorithms Using Java Pseudocode
200418
19 201717
20 200717

About Richard E. Neapolitan

Richard E. Neapolitan is a scholar working on Artificial Intelligence, Management Science and Operations Research, Molecular Biology, Genetics and Computational Theory and Mathematics, having authored 56 papers that have together received 1.6k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (16 papers), AI-based Problem Solving and Planning (9 papers), Genetic Associations and Epidemiology (6 papers), Bioinformatics and Genomic Networks (5 papers), Gene expression and cancer classification (4 papers), Multi-Criteria Decision Making (3 papers), Psychometric Methodologies and Testing (3 papers) and Forecasting Techniques and Applications (2 papers). The work is most often cited by research in Artificial Intelligence (725 citations), Management Science and Operations Research (172 citations), Software (37 citations), Signal Processing (99 citations) and General Decision Sciences (16 citations). Richard E. Neapolitan has collaborated with scholars based in United States, Philippines and South Korea. Frequent co-authors include Peter M. Jones, Xia Jiang, Shyam Visweswaran, M. Michael Barmada, Xia Jiang, Zexian Zeng, Scott B. Morris, Adam Brufsky, Alan Wells and Michael Bass. Their work appears in journals such as PLoS ONE, BMC Bioinformatics, Journal of the American Medical Informatics Association, Applied Artificial Intelligence and Mathematical Biosciences.

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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