Paolo Rosso
- Artificial Intelligence top 10%
- Transportation top 5%
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Philippe Cudré-MaurouxDingqi YangBin LiPengyang WangBingqing QuKarim BouzoubaaKurt StockingerYuhuan Lu
- Topics
- Advanced Graph Neural Networks (7 papers)Topic Modeling (6 papers)Complex Network Analysis Techniques (4 papers)
- Journals
- IEEE Transactions on Knowledge and Data EngineeringProcesamiento del lenguaje naturalZürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
- Partner nations
- SwitzerlandMacaoChina
In The Last Decade
Paolo Rosso
14 papers receiving 290 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 182
- Transportation 95
- Information Systems 87
- Computer Vision and Pattern Recognition 45
- Statistical and Nonlinear Physics 42
Countries citing papers authored by Paolo Rosso
This map shows the geographic impact of Paolo Rosso'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 Paolo Rosso with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paolo Rosso more than expected).
Fields of papers citing papers by Paolo Rosso
This network shows the impact of papers produced by Paolo Rosso. 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 Paolo Rosso. The network helps show where Paolo Rosso may publish in the future.
Co-authorship network of co-authors of Paolo Rosso
This figure shows the co-authorship network connecting the top 25 collaborators of Paolo Rosso. A scholar is included among the top collaborators of Paolo Rosso 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 Paolo Rosso. Paolo Rosso is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 14 | |
| 5 | 4 | |
| 6 | 124 | |
| 7 | 5 | |
| 8 | 77 | |
| 9 | 6 | |
| 10 | 40 | |
| 11 | TextMess 2.0: las tecnologías del lenguaje humano ante los nuevos retos de la comunicación digital | 1 |
| 12 | Drug-Drug Interaction Detection: A New Approach Based on Maximal Frequent Sequences | 7 |
| 13 | Un Análisis Comparativo de Estrategias para la Categorización Semántica de Textos Cortos | 1 |
| 14 | Systeme de Question/Reponse dans le cadre d'une plateforme integree : cas de l'Arabe | 2 |
| 15 | Spam Detection and Email Classification | 0 |
| 16 | Catone Sacco e l’Umanesimo lombardo. Notizie e documenti | 1 |
About Paolo Rosso
Paolo Rosso is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Information Systems, having authored 16 papers that have together received 292 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (7 papers), Topic Modeling (6 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Transportation (95 citations), Artificial Intelligence (182 citations) and Computational Mathematics (3 citations). Paolo Rosso has collaborated with scholars based in Switzerland, Macao and China. Frequent co-authors include Philippe Cudré-Mauroux, Dingqi Yang, Bin Li, Pengyang Wang, Bingqing Qu, Karim Bouzoubaa, Kurt Stockinger, Yuhuan Lu, Luís Alfonso Ureña López and Marcelo Luis Errecalde. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Procesamiento del lenguaje natural and Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences).
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.