Donatella Firmani
- Artificial Intelligence top 5%
- Management Science and Operations Research top 5%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Paolo MerialdoAndrea RossiDenilson BarbosaDivesh SrivastavaBarna SahaMassimo MecellaCarlo BatiniMonica Scannapieco
- Topics
- Data Quality and Management (11 papers)Complex Network Analysis Techniques (8 papers)Topic Modeling (7 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceStatistical and Nonlinear Physics
- Partner nations
- ItalyUnited StatesCanada
In The Last Decade
Donatella Firmani
37 papers receiving 630 citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 423
- Management Science and Operations Research 200
- Information Systems 133
- Computer Networks and Communications 98
- Computer Vision and Pattern Recognition 85
Countries citing papers authored by Donatella Firmani
This map shows the geographic impact of Donatella Firmani'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 Donatella Firmani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Donatella Firmani more than expected).
Fields of papers citing papers by Donatella Firmani
This network shows the impact of papers produced by Donatella Firmani. 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 Donatella Firmani. The network helps show where Donatella Firmani may publish in the future.
Co-authorship network of co-authors of Donatella Firmani
This figure shows the co-authorship network connecting the top 25 collaborators of Donatella Firmani. A scholar is included among the top collaborators of Donatella Firmani 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 Donatella Firmani. Donatella Firmani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 22 | |
| 5 | 9 | |
| 6 | 1 | |
| 7 | 9 | |
| 8 | 8 | |
| 9 | Knowledge Graph Embedding for Link Predictionbreakdown → | 251 |
| 10 | 6 | |
| 11 | 2 | |
| 12 | Robust Entity Resolution Using a CrowdOracle. | 4 |
| 13 | 38 | |
| 14 | 4 | |
| 15 | 16 | |
| 16 | 12 | |
| 17 | Large-Scale Graph Biconnectivity in MapReduce | 2 |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 1 |
About Donatella Firmani
Donatella Firmani is a scholar working on Management Science and Operations Research, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 37 papers that have together received 651 indexed citations. Recurring topics across this work include Data Quality and Management (11 papers), Complex Network Analysis Techniques (8 papers) and Topic Modeling (7 papers). The work is most often cited by research in Management Science and Operations Research (200 citations), Artificial Intelligence (423 citations) and Statistical and Nonlinear Physics (80 citations). Donatella Firmani has collaborated with scholars based in Italy, United States and Canada. Frequent co-authors include Paolo Merialdo, Andrea Rossi, Denilson Barbosa, Divesh Srivastava, Barna Saha, Massimo Mecella, Carlo Batini, Monica Scannapieco, Riccardo Torlone and Graham Cormode. Their work appears in journals such as Proceedings of the VLDB Endowment, Information Processing & Management and ACM SIGMOD Record.
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.