Jim Prentzas

1.1k total citations
44 papers, 530 citations indexed

About

Jim Prentzas is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Jim Prentzas has authored 44 papers receiving a total of 530 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 14 papers in Information Systems and 11 papers in Computational Theory and Mathematics. Recurrent topics in Jim Prentzas's work include Neural Networks and Applications (16 papers), Fuzzy Logic and Control Systems (13 papers) and Rough Sets and Fuzzy Logic (11 papers). Jim Prentzas is often cited by papers focused on Neural Networks and Applications (16 papers), Fuzzy Logic and Control Systems (13 papers) and Rough Sets and Fuzzy Logic (11 papers). Jim Prentzas collaborates with scholars based in Greece and United Kingdom. Jim Prentzas's co-authors include Ioannis Hatzilygeroudis, Christos Makris, Constantinos Koutsojannis, Spyros Sioutas, John Garofalakis, Athanasios Tsakalidis, Angelos Markos, Grigorios N. Beligiannis, Konstantinos Kovas and Vasile Palade and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Knowledge and Data Engineering and Computers Environment and Urban Systems.

In The Last Decade

Jim Prentzas

39 papers receiving 471 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jim Prentzas Greece 13 319 142 65 59 31 44 530
Ngo Tung Son Vietnam 15 141 0.4× 103 0.7× 49 0.8× 37 0.6× 15 0.5× 58 523
Sathiamoorthy Manoharan New Zealand 11 154 0.5× 217 1.5× 64 1.0× 21 0.4× 13 0.4× 82 610
Elena Gaudioso Spain 13 159 0.5× 191 1.3× 112 1.7× 19 0.3× 10 0.3× 34 513
Pragya Dwivedi India 14 285 0.9× 244 1.7× 138 2.1× 21 0.4× 52 1.7× 33 795
Andrew Kwok-Fai Lui Hong Kong 12 162 0.5× 78 0.5× 76 1.2× 35 0.6× 12 0.4× 43 406
Abdulqader M. Mohsen Yemen 9 228 0.7× 55 0.4× 22 0.3× 47 0.8× 35 1.1× 23 461
Tom Lunney United Kingdom 10 144 0.5× 128 0.9× 27 0.4× 13 0.2× 21 0.7× 45 485
Fei Xu China 12 189 0.6× 100 0.7× 22 0.3× 24 0.4× 13 0.4× 77 570
Nur Ulfa Maulidevi Indonesia 13 288 0.9× 172 1.2× 16 0.2× 22 0.4× 13 0.4× 77 681
Daniel W. Lewis United States 4 85 0.3× 63 0.4× 18 0.3× 25 0.4× 11 0.4× 11 410

Countries citing papers authored by Jim Prentzas

Since Specialization
Citations

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

Fields of papers citing papers by Jim Prentzas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jim Prentzas. 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 Jim Prentzas. The network helps show where Jim Prentzas may publish in the future.

Co-authorship network of co-authors of Jim Prentzas

This figure shows the co-authorship network connecting the top 25 collaborators of Jim Prentzas. A scholar is included among the top collaborators of Jim Prentzas 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 Jim Prentzas. Jim Prentzas 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.
Prentzas, Jim, et al.. (2025). Explainable Artificial Intelligence Approaches in Primary Education: A Review. Electronics. 14(11). 2279–2279. 2 indexed citations
2.
Prentzas, Jim & Ioannis Hatzilygeroudis. (2021). Neurules and connectionist expert systems: Unexplored neuro-symbolic reasoning aspects. Intelligent Decision Technologies. 15(4). 761–777. 2 indexed citations
3.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2021). AI Approaches for the Prognosis of the Survival (or Not) of Patients with Bone Metastases. 1353–1357. 1 indexed citations
4.
Kovas, Konstantinos, et al.. (2019). An Approach using Certainty Factor Rules for Aphasia Diagnosis. 1–7. 10 indexed citations
5.
Hatzilygeroudis, Ioannis, Vasile Palade, & Jim Prentzas. (2016). Combinations of Intelligent Methods and Applications. Smart innovation, systems and technologies. 4 indexed citations
6.
Prentzas, Jim & Ioannis Hatzilygeroudis. (2014). Improving efficiency of merging symbolic rules into integrated rules: splitting methods and mergability criteria. Expert Systems. 32(2). 244–260. 1 indexed citations
7.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2010). A Survey on Recent Patents Regarding Intelligent Educational Systems. Recent Patents on Computer Science. 2(3). 214–222. 1 indexed citations
8.
Prentzas, Jim & Ioannis Hatzilygeroudis. (2009). Combinations of case-based reasoning with other intelligent methods. International Journal of Hybrid Intelligent Systems. 6(4). 189–209. 18 indexed citations
9.
Prentzas, Jim & Ioannis Hatzilygeroudis. (2007). Categorizing approaches combining rule‐based and case‐based reasoning. Expert Systems. 24(2). 97–122. 89 indexed citations
10.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2005). Neuro-Symbolic Approaches for Knowledge Representation in Expert Systems. International Journal of Hybrid Intelligent Systems. 1(3-4). 111–126. 17 indexed citations
11.
Prentzas, Jim, Ioannis Hatzilygeroudis, & A. Tsakalidis. (2003). Updating a hybrid rule base with new empirical source knowledge. 9–15. 4 indexed citations
12.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2003). Integrating (rules, neural networks) and cases for knowledge representation and reasoning in expert systems. Expert Systems with Applications. 27(1). 63–75. 36 indexed citations
13.
Prentzas, Jim & Ioannis Hatzilygeroudis. (2002). Intelligent Educational Systems for Individualized Learning. 1 indexed citations
14.
Prentzas, Jim & Ioannis Hatzilygeroudis. (2002). Updating a hybrid rule base with changes to its symbolic source knowledge. European Conference on Artificial Intelligence. 71(5). 250–254. 3 indexed citations
15.
Prentzas, Jim, Ioannis Hatzilygeroudis, & Constantinos Koutsojannis. (2002). A Web-based ITS controlled by a hybrid expert system. 239–240. 10 indexed citations
16.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2001). HYMES: A HYbrid Modular Expert System with Efficient Inference and Explanation. 7 indexed citations
17.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2001). An Efficient Hybrid Rule Based Inference Engine with Explanation Capability. The Florida AI Research Society. 227–231. 7 indexed citations
18.
Prentzas, Jim, et al.. (2001). Architectural Aspects of a Web-Based ITS for Teaching New Information Technologies. EdMedia: World Conference on Educational Media and Technology. 2001(1). 1516–1521. 1 indexed citations
19.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2000). Producing Modular Hybrid Rule Bases for Expert Systems. The Florida AI Research Society. 181–185. 4 indexed citations
20.
Hatzilygeroudis, Ioannis & Jim Prentzas. (2000). NEURULES: INTEGRATING SYMBOLIC RULES AND NEUROCOMPUTING. 122–133. 4 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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