Diego Ceccarelli
- Artificial Intelligence top 10%
- Information Systems top 10%
- Management Science and Operations Research top 10%
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Co-authors
- Raffaele PeregoClaudio LuccheseSalvatore OrlandoGiovanni TummarelloRenaud DelbruFabrizio SilvestriRoi BlancoMiles Osborne
- Topics
- Topic Modeling (9 papers)Natural Language Processing Techniques (5 papers)Advanced Graph Neural Networks (4 papers)
- Journals
- Computational IntelligenceACM SIGIR ForumIRIS Research product catalog (Sapienza University of Rome)
- Partner nations
- ItalySpainUnited Kingdom
In The Last Decade
Diego Ceccarelli
15 papers receiving 191 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 169
- Information Systems 69
- Management Science and Operations Research 47
- Computer Networks and Communications 34
- Computer Vision and Pattern Recognition 18
Countries citing papers authored by Diego Ceccarelli
This map shows the geographic impact of Diego Ceccarelli'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 Diego Ceccarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Ceccarelli more than expected).
Fields of papers citing papers by Diego Ceccarelli
This network shows the impact of papers produced by Diego Ceccarelli. 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 Diego Ceccarelli. The network helps show where Diego Ceccarelli may publish in the future.
Co-authorship network of co-authors of Diego Ceccarelli
This figure shows the co-authorship network connecting the top 25 collaborators of Diego Ceccarelli. A scholar is included among the top collaborators of Diego Ceccarelli 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 Diego Ceccarelli. Diego Ceccarelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 17 | |
| 3 | 6 | |
| 4 | 3 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | Dexter 2.0: an open source tool for semantically enriching data | 7 |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 38 | |
| 12 | 46 | |
| 13 | 2 | |
| 14 | 15 | |
| 15 | 42 | |
| 16 | Discovering Europeana users’ search behavior | 1 |
| 17 | 16 |
About Diego Ceccarelli
Diego Ceccarelli is a scholar working on Artificial Intelligence, Information Systems and Computer Science Applications, having authored 17 papers that have together received 209 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (5 papers) and Advanced Graph Neural Networks (4 papers). The work is most often cited by research in Artificial Intelligence (169 citations), Management Science and Operations Research (47 citations) and Information Systems (69 citations). Diego Ceccarelli has collaborated with scholars based in Italy, Spain and United Kingdom. Frequent co-authors include Raffaele Perego, Claudio Lucchese, Salvatore Orlando, Giovanni Tummarello, Renaud Delbru, Fabrizio Silvestri, Roi Blanco, Miles Osborne, Leif Azzopardi and Martin Halvey. Their work appears in journals such as Computational Intelligence, ACM SIGIR Forum and IRIS Research product catalog (Sapienza University of Rome).
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.