Silviu Paun
- Artificial Intelligence top 5%
- Computer Science Applications top 5%
- Computer Vision and Pattern Recognition
- Information Systems
- Sociology and Political Science
- Co-authors
- Massimo PoesioDirk HovyBarbara PlankTommaso FornaciariJon ChamberlainUdo KruschwitzJuntao YuBob Carpenter
- Topics
- Topic Modeling (14 papers)Natural Language Processing Techniques (9 papers)Speech and dialogue systems (8 papers)
- Journals
- Journal of Artificial Intelligence ResearchTransactions of the Association for Computational LinguisticsAnnual Review of Linguistics
- Partner nations
- United KingdomItalyGermany
In The Last Decade
Silviu Paun
17 papers receiving 308 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 299
- Computer Science Applications 53
- Computer Vision and Pattern Recognition 38
- Information Systems 32
- Sociology and Political Science 29
Countries citing papers authored by Silviu Paun
This map shows the geographic impact of Silviu Paun'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 Silviu Paun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silviu Paun more than expected).
Fields of papers citing papers by Silviu Paun
This network shows the impact of papers produced by Silviu Paun. 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 Silviu Paun. The network helps show where Silviu Paun may publish in the future.
Co-authorship network of co-authors of Silviu Paun
This figure shows the co-authorship network connecting the top 25 collaborators of Silviu Paun. A scholar is included among the top collaborators of Silviu Paun 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 Silviu Paun. Silviu Paun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 6 | |
| 5 | 8 | |
| 6 | 9 | |
| 7 | 40 | |
| 8 | 67 | |
| 9 | 7 | |
| 10 | 3 | |
| 11 | 42 | |
| 12 | 26 | |
| 13 | 6 | |
| 14 | Aggregation Driven Progression System for GWAPs | 2 |
| 15 | 34 | |
| 16 | 3 | |
| 17 | 3 | |
| 18 | 51 | |
| 19 | 14 |
About Silviu Paun
Silviu Paun is a scholar working on Computer Science Applications, Artificial Intelligence and Family Practice, having authored 19 papers that have together received 324 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (9 papers) and Speech and dialogue systems (8 papers). The work is most often cited by research in Computer Science Applications (53 citations), Artificial Intelligence (299 citations) and Communication (17 citations). Silviu Paun has collaborated with scholars based in United Kingdom, Italy and Germany. Frequent co-authors include Massimo Poesio, Dirk Hovy, Barbara Plank, Tommaso Fornaciari, Jon Chamberlain, Udo Kruschwitz, Juntao Yu, Bob Carpenter, Valerio Basile and Michael J. Fell. Their work appears in journals such as Journal of Artificial Intelligence Research, Transactions of the Association for Computational Linguistics and Annual Review of Linguistics.
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.