Matteo Riondato
- Artificial Intelligence top 5%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Statistical and Nonlinear Physics top 2%
- Signal Processing top 5%
- Co-authors
- Eli UpfalEvgenios M. KornaropoulosUğur ÇetintemelMert AkdereStanley B. ZdonikFrancesco BonchiLorenzo De StefaniAlessandro Epasto
- Topics
- Data Mining Algorithms and Applications (17 papers)Rough Sets and Fuzzy Logic (12 papers)Complex Network Analysis Techniques (11 papers)
- Partner nations
- United StatesItalySpain
In The Last Decade
Matteo Riondato
37 papers receiving 773 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 418
- Information Systems 303
- Computer Networks and Communications 288
- Statistical and Nonlinear Physics 280
- Signal Processing 183
Countries citing papers authored by Matteo Riondato
This map shows the geographic impact of Matteo Riondato'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 Matteo Riondato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Riondato more than expected).
Fields of papers citing papers by Matteo Riondato
This network shows the impact of papers produced by Matteo Riondato. 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 Matteo Riondato. The network helps show where Matteo Riondato may publish in the future.
Co-authorship network of co-authors of Matteo Riondato
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Riondato. A scholar is included among the top collaborators of Matteo Riondato 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 Matteo Riondato. Matteo Riondato is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 7 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 11 | |
| 9 | 6 | |
| 10 | 10 | |
| 11 | Sharp uniform convergence bounds through empirical centralization | 2 |
| 12 | 19 | |
| 13 | 40 | |
| 14 | 45 | |
| 15 | 3 | |
| 16 | 37 | |
| 17 | 20 | |
| 18 | Finding the True Frequent Itemsets∗ | 14 |
| 19 | 44 | |
| 20 | 31 |
About Matteo Riondato
Matteo Riondato is a scholar working on Statistical and Nonlinear Physics, Computational Theory and Mathematics and Information Systems, having authored 39 papers that have together received 801 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (17 papers), Rough Sets and Fuzzy Logic (12 papers) and Complex Network Analysis Techniques (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (280 citations), Signal Processing (183 citations) and Information Systems (303 citations). Matteo Riondato has collaborated with scholars based in United States, Italy and Spain. Frequent co-authors include Eli Upfal, Evgenios M. Kornaropoulos, Uğur Çetintemel, Mert Akdere, Stanley B. Zdonik, Francesco Bonchi, Lorenzo De Stefani, Alessandro Epasto, Rodrigo Fonseca and David García-Soriano. Their work appears in journals such as Machine Learning, Data Mining and Knowledge Discovery and Knowledge and Information 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.