Francesco Bergadano

68 papers receiving 945 citations

Peers

Francesco Bergadano
Comparison fields: 5 of 87
  • Information Systems 531
  • Artificial Intelligence 500
  • Signal Processing 367
  • Computer Networks and Communications 196
  • Computational Theory and Mathematics 169
Replace Claudia Picardi with:
Claudia Picardi Italy
Donald E. Porter United States
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Sudhir Aggarwal United States
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Francesco Bergadano relative to Claudia Picardi Italy Claudia Picardi's profile →
Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Francesco Bergadano

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Bergadano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Bergadano

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Bergadano. A scholar is included among the top collaborators of Francesco Bergadano 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 Francesco Bergadano. Francesco Bergadano 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
#WorkIndexed citations
1 1
2 0
3 1
4 10
5 3
6
Digital privacy: tecnologie "conformate" e regole giuridiche
1
7
On Learning Programs and Small Depth Circuits
1
8 13
9
Intelligent Agents: a Tool for Managing and Retrieving Information in Distributed Systems
1
10
Learning Multivariate Polynomials from Substitution and Equivalence Queries
4
11 38
12 0
13
An Interactive System to Learn Functional Logic Programs.
23
14
The problem of induction and machine learning
5
15
Machine learning: an integrated framework and its applications
15
16
Integrated Learning in a Real Domain.
1
17 2
18
Concept Acquisition in an Integrated EBL and SBL Environment.
1
19
Integrating EBL and SBL approaches to knowledge base refinement
1
20 2

About Francesco Bergadano

Francesco Bergadano is a scholar working on Artificial Intelligence, Software and Signal Processing, having authored 74 papers that have together received 1.1k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (15 papers), Advanced Malware Detection Techniques (13 papers) and Semantic Web and Ontologies (9 papers). The work is most often cited by research in Signal Processing (367 citations), Information Systems (531 citations) and Human-Computer Interaction (127 citations). Francesco Bergadano has collaborated with scholars based in Italy, United States and Belgium. Frequent co-authors include Daniele Gunetti, Claudia Picardi, Bruno Crispo, Lorenza Saitta, Stefano Varricchio, Attilio Giordana, Ryszard S. Michalski, Stan Matwin, Davide Cavagnino and Jiaxing Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Information Sciences and IEEE Transactions on Fuzzy Systems.

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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