Fabrizio Silvestri
- Information Systems top 0.2%
- Web Data Mining and Analysis 38
- Recommender Systems and Techniques 35
- Information Retrieval and Search Behavior 15
- Signal Processing top 1%
- Data Management and Algorithms 26
- Artificial Intelligence top 1%
- Advanced Graph Neural Networks 15
- Topic Modeling 14
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- Caching and Content Delivery 26
- Advanced Database Systems and Queries 13
- Co-authors
- Raffaele PeregoSalvatore OrlandoRanieri BaragliaRicardo Baeza‐YatesVanessa MurdockAristides GionisClaudio LuccheseCarlos Castillo
- Journals
- SHILAP Revista de lepidopterología (1 paper)Communications of the ACM (1 paper)IEEE Access (2 papers)
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Fabrizio Silvestri
139 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 106
- Information Systems 1.6k
- Signal Processing 547
- Artificial Intelligence 1.2k
- Computer Networks and Communications 860
- Computer Vision and Pattern Recognition 598
Countries citing papers authored by Fabrizio Silvestri
This map shows the geographic impact of Fabrizio Silvestri'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 Fabrizio Silvestri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabrizio Silvestri more than expected).
Fields of papers citing papers by Fabrizio Silvestri
This network shows the impact of papers produced by Fabrizio Silvestri. 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 Fabrizio Silvestri. The network helps show where Fabrizio Silvestri may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fabrizio Silvestri, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 2 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 7 | |
| 8 | 2024 | 4 | |
| 9 | 2023 | 11 | |
| 10 | 2023 | 3 | |
| 11 | 2023 | 11 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 4 | |
| 14 | 2022 | 13 | |
| 15 | 2021 | 48 | |
| 16 | Blog distillation via sentiment-sensitive link analysis | 2011 | 1 |
| 17 | 2011 | 1 | |
| 18 | 2007 | 11 | |
| 19 | A Hybrid Strategy for Caching Web Search Engine Results. | 2003 | 1 |
| 20 | A Hybrid Strategy for Caching Web Search Engine Results | 2003 | 1 |
About Fabrizio Silvestri
Fabrizio Silvestri is a scholar working on Information Systems, Signal Processing and Computer Networks and Communications, having authored 150 papers that have together received 2.9k indexed citations. Recurring topics across this work include Web Data Mining and Analysis (38 papers), Recommender Systems and Techniques (35 papers), Data Management and Algorithms (26 papers), Caching and Content Delivery (26 papers), Advanced Graph Neural Networks (15 papers), Information Retrieval and Search Behavior (15 papers), Topic Modeling (14 papers) and Advanced Database Systems and Queries (13 papers). The work is most often cited by research in Information Systems (1.6k citations), Signal Processing (547 citations) and Artificial Intelligence (1.2k citations). Fabrizio Silvestri has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Raffaele Perego, Salvatore Orlando, Ranieri Baraglia, Ricardo Baeza‐Yates, Vanessa Murdock, Aristides Gionis, Claudio Lucchese, Carlos Castillo, Franco Maria Nardini and Gabriele Tolomei. Their work appears in journals such as SHILAP Revista de lepidopterología, Communications of the ACM and IEEE Access.
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.