Stefano Faralli
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Advanced Graph Neural Networks
-
- Online Learning and Analytics
Papers in
-
- Topic Modeling 23
- Natural Language Processing Techniques 19
- Semantic Web and Ontologies 11
- Advanced Graph Neural Networks 6
-
- Biomedical Text Mining and Ontologies 10
- Co-authors
- Roberto Navigli (9 shared papers)Paola Velardi (22 shared papers)Damiano Distante (9 shared papers)Giovanni Stilo (12 shared papers)Simone Paolo Ponzetto (12 shared papers)Paul Buitelaar (1 shared paper)Georgeta Bordea (1 shared paper)Alexander Panchenko (5 shared papers)
In The Last Decade
Stefano Faralli
52 papers receiving 742 citations
Peers
Comparison fields: 5 of 89
- Artificial Intelligence 594
- Computer Science Applications 100
- Information Systems 133
- Communication 27
- Statistical and Nonlinear Physics 45
Countries citing papers authored by Stefano Faralli
This map shows the geographic impact of Stefano Faralli'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 Stefano Faralli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Faralli more than expected).
Fields of papers citing papers by Stefano Faralli
This network shows the impact of papers produced by Stefano Faralli. 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 Stefano Faralli. The network helps show where Stefano Faralli may publish in the future.
Co-authors
The 25 scholars most cited alongside Stefano Faralli, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 132 | |
| 2 | 2011 | 89 | |
| 3 | 2020 | 83 | |
| 4 | 2015 | 58 | |
| 5 | 2016 | 39 | |
| 6 | 2011 | 39 | |
| 7 | 2016 | 37 | |
| 8 | A New Minimally-Supervised Framework for Domain Word Sense Disambiguation | 2012 | 27 |
| 9 | 2023 | 20 | |
| 10 | Large scale homophily analysis in twitter using a twixonomy | 2015 | 19 |
| 11 | 2021 | 18 | |
| 12 | 2020 | 18 | |
| 13 | 2017 | 17 | |
| 14 | GlossBoot: Bootstrapping Multilingual Domain Glossaries from the Web | 2013 | 14 |
| 15 | 2017 | 13 | |
| 16 | 2017 | 12 | |
| 17 | 2018 | 11 | |
| 18 | 2017 | 11 | |
| 19 | 2015 | 10 | |
| 20 | 2020 | 10 |
About Stefano Faralli
Stefano Faralli is a scholar working on Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics, Information Systems and Computer Vision and Pattern Recognition, having authored 58 papers that have together received 796 indexed citations. Recurring topics across this work include Topic Modeling (23 papers), Natural Language Processing Techniques (19 papers), Semantic Web and Ontologies (11 papers), Biomedical Text Mining and Ontologies (10 papers), Complex Network Analysis Techniques (9 papers), Advanced Graph Neural Networks (6 papers), Recommender Systems and Techniques (5 papers) and Wikis in Education and Collaboration (4 papers). The work is most often cited by research in Artificial Intelligence (594 citations), Computer Science Applications (100 citations), Information Systems (133 citations), Communication (27 citations) and Statistical and Nonlinear Physics (45 citations). Stefano Faralli has collaborated with scholars based in Italy, Germany and Spain. Frequent co-authors include Roberto Navigli, Paola Velardi, Damiano Distante, Giovanni Stilo, Simone Paolo Ponzetto, Paul Buitelaar, Georgeta Bordea, Alexander Panchenko, Chris Biemann and Heiko Paulheim. Their work appears in journals such as Language Resources and Evaluation, Applied Sciences, ACM Computing Surveys, ACM SIGIR Forum and Cognitive Computation.
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.