Donatella Firmani

1.3k total citations · 1 hit paper
37 papers, 651 citations indexed

About

Donatella Firmani is a scholar working on Artificial Intelligence, Computer Networks and Communications and Management Science and Operations Research. According to data from OpenAlex, Donatella Firmani has authored 37 papers receiving a total of 651 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 13 papers in Computer Networks and Communications and 11 papers in Management Science and Operations Research. Recurrent topics in Donatella Firmani's work include Data Quality and Management (11 papers), Complex Network Analysis Techniques (8 papers) and Topic Modeling (7 papers). Donatella Firmani is often cited by papers focused on Data Quality and Management (11 papers), Complex Network Analysis Techniques (8 papers) and Topic Modeling (7 papers). Donatella Firmani collaborates with scholars based in Italy, United States and Canada. Donatella Firmani's co-authors include Paolo Merialdo, Andrea Rossi, Denilson Barbosa, Divesh Srivastava, Barna Saha, Massimo Mecella, Monica Scannapieco, Carlo Batini, Riccardo Torlone and Graham Cormode and has published in prestigious journals such as Proceedings of the VLDB Endowment, Information Processing & Management and ACM SIGMOD Record.

In The Last Decade

Donatella Firmani

37 papers receiving 630 citations

Hit Papers

Knowledge Graph Embedding for Link Prediction 2021 2026 2022 2024 2021 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Donatella Firmani Italy 11 423 200 133 98 85 37 651
Nitish Korula United States 10 258 0.6× 124 0.6× 93 0.7× 133 1.4× 31 0.4× 26 491
Achim Rettinger Germany 14 470 1.1× 128 0.6× 173 1.3× 67 0.7× 80 0.9× 50 645
Alantha Newman France 5 232 0.5× 109 0.5× 66 0.5× 87 0.9× 48 0.6× 17 497
Weiwen Liu China 16 448 1.1× 94 0.5× 367 2.8× 58 0.6× 164 1.9× 54 750
Francesco Folino Italy 12 238 0.6× 86 0.4× 154 1.2× 161 1.6× 50 0.6× 46 570
Sujith Ravi United States 15 498 1.2× 43 0.2× 177 1.3× 159 1.6× 104 1.2× 24 809
Mehrnoush Shamsfard Iran 15 765 1.8× 63 0.3× 353 2.7× 74 0.8× 103 1.2× 77 927
Atsuyoshi Nakamura Japan 8 129 0.3× 63 0.3× 152 1.1× 75 0.8× 48 0.6× 47 384
Anastasia Dimou Belgium 10 363 0.9× 142 0.7× 170 1.3× 132 1.3× 55 0.6× 67 534
Saravanan Thirumuruganathan United States 16 436 1.0× 304 1.5× 196 1.5× 209 2.1× 95 1.1× 62 831

Countries citing papers authored by Donatella Firmani

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Firmani, Donatella, et al.. (2023). NLP-Based Management of Large Multiple-Choice Test Item Repositories. Journal of Learning Analytics. 10(3). 28–44. 2 indexed citations
2.
Mazzei, Maurizio, Paolo Merialdo, Giovanni Simonini, et al.. (2023). Experiences and Lessons Learned from the SIGMOD Entity Resolution Programming Contests. ACM SIGMOD Record. 52(2). 43–47. 1 indexed citations
3.
Firmani, Donatella, et al.. (2022). Managing Large Multiple-choice Test Items Repositories. 1254. 275–279. 1 indexed citations
4.
Firmani, Donatella, et al.. (2022). Effective Explanations for Entity Resolution Models. 2022 IEEE 38th International Conference on Data Engineering (ICDE). 2709–2721. 9 indexed citations
5.
Firmani, Donatella, et al.. (2022). Self-supervised learning for medieval handwriting identification: A case study from the Vatican Apostolic Library. Information Processing & Management. 59(3). 102875–102875. 9 indexed citations
6.
Galhotra, Sainyam, Donatella Firmani, Barna Saha, & Divesh Srivastava. (2022). Hierarchical Entity Resolution using an Oracle. Proceedings of the 2022 International Conference on Management of Data. 414–428. 1 indexed citations
7.
Rossi, Andrea, et al.. (2022). Explaining Link Prediction Systems based on Knowledge Graph Embeddings. Proceedings of the 2022 International Conference on Management of Data. 2062–2075. 22 indexed citations
8.
Firmani, Donatella, et al.. (2021). In Codice Ratio: A crowd-enabled solution for low resource machine transcription of the Vatican Registers. Information Processing & Management. 58(5). 102606–102606. 8 indexed citations
9.
Rossi, Andrea, et al.. (2021). Knowledge Graph Embedding for Link Prediction. ACM Transactions on Knowledge Discovery from Data. 15(2). 1–49. 251 indexed citations breakdown →
10.
Galhotra, Sainyam, Donatella Firmani, Barna Saha, & Divesh Srivastava. (2021). BEER. IRIS Research product catalog (Sapienza University of Rome). 2711–2715. 6 indexed citations
11.
Firmani, Donatella, Sainyam Galhotra, Barna Saha, & Divesh Srivastava. (2018). Robust Entity Resolution Using a CrowdOracle.. IEEE Data(base) Engineering Bulletin. 41. 91–103. 4 indexed citations
12.
Galhotra, Sainyam, Donatella Firmani, Barna Saha, & Divesh Srivastava. (2018). Robust Entity Resolution using Random Graphs. IRIS Research product catalog (Sapienza University of Rome). 3–18. 15 indexed citations
13.
Conte, Alessio, et al.. (2017). Fast Enumeration of Large k-Plexes. CINECA IRIS Institutial research information system (University of Pisa). 115–124. 38 indexed citations
14.
Firmani, Donatella, et al.. (2015). Strong Articulation Points and Strong Bridges in Large Scale Graphs. Algorithmica. 74(3). 1123–1147. 4 indexed citations
15.
Cormode, Graham & Donatella Firmani. (2013). A unifying framework for ℓ 0-sampling algorithms. Distributed and Parallel Databases. 32(3). 315–335. 16 indexed citations
16.
Ausiello, Giorgio, Donatella Firmani, & Luigi Laura. (2013). The (betweenness) centrality of critical nodes and network cores. IRIS Research product catalog (Sapienza University of Rome). 90–95. 12 indexed citations
17.
Ausiello, Giorgio, et al.. (2012). Large-Scale Graph Biconnectivity in MapReduce. RePEc: Research Papers in Economics. 4(4). 2 indexed citations
18.
Ausiello, Giorgio, Donatella Firmani, & Luigi Laura. (2012). Real-time analysis of critical nodes in network cores. IRIS Research product catalog (Sapienza University of Rome). 1930. 42–46. 1 indexed citations
19.
Ausiello, Giorgio, Camil Demetrescu, Irene Finocchi, & Donatella Firmani. (2012). k-Calling context profiling. ACM SIGPLAN Notices. 47(10). 867–878. 1 indexed citations
20.
Ausiello, Giorgio, Donatella Firmani, & Luigi Laura. (2012). Real‐time monitoring of undirected networks: Articulation points, bridges, and connected and biconnected components. Networks. 59(3). 275–288. 7 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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