Simone Bassis

506 citations
54 papers · 355 · h-index 10

Impact in

Papers in

Simone Bassis

50 papers receiving 344 citations

Peers

Simone Bassis
Comparison fields: 5 of 101
  • Statistics and Probability 50
  • Artificial Intelligence 135
  • Management Science and Operations Research 49
  • Computational Theory and Mathematics 50
  • Statistics, Probability and Uncertainty 15
Replace Anastasios N. Angelopoulos with:
Anastasios N. Angelopoulos United States
Maxim Panov Russia
Seppo Virtanen Finland
Akhtar Rasool India
Tian Gao United States
Bo Chang Canada
Michael Valko United States
Jan Lemeire Belgium
Eunho Yang South Korea
Simone Bassis relative to Anastasios N. Angelopoulos United States Anastasios N. Angelopoulos's profile →
Citations per field
00.5×10×20×30×38×
Anastasios N. Angelopoulos · 1×
Citations per year

Countries citing papers authored by Simone Bassis

Since Specialization
Citations

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

Fields of papers citing papers by Simone Bassis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201671
2 201645
3 201638
4 200820
5 201216
6 200914
7 201612
8 200912
9 200510
10 200710
11 200810
12 20089
13 20076
14 20076
15 20155
16 20115
17
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
20114
18 20054
19 20074
20 20024

About Simone Bassis

Simone Bassis is a scholar working on Artificial Intelligence, Statistics and Probability, Computational Theory and Mathematics, Management Science and Operations Research and Computer Networks and Communications, having authored 54 papers that have together received 355 indexed citations. Recurring topics across this work include Neural Networks and Applications (13 papers), Machine Learning and Algorithms (10 papers), Rough Sets and Fuzzy Logic (5 papers), Machine Learning and Data Classification (4 papers), Fuzzy Logic and Control Systems (4 papers), Advanced Algebra and Logic (3 papers), Cognitive Science and Mapping (3 papers) and Gene expression and cancer classification (3 papers). The work is most often cited by research in Statistics and Probability (50 citations), Artificial Intelligence (135 citations), Management Science and Operations Research (49 citations), Computational Theory and Mathematics (50 citations) and Statistics, Probability and Uncertainty (15 citations). Simone Bassis has collaborated with scholars based in Italy, Switzerland and Canada. Frequent co-authors include Bruno Apolloni, Anna Aurelia Esposito, Francesco Carlo Morabito, Dario Malchiodi, Eros Gian Alessandro Pasero, Witold Pedrycz, Sabrina Gaito, Chiara Locatelli, Serena Crosara and Cecilia Quintavalla. Their work appears in journals such as Information Sciences, Nonlinear Analysis, Nonlinear Analysis Hybrid Systems, Journal of Veterinary Internal Medicine and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).

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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