Marco Dinarelli
- Artificial Intelligence top 5%
- Signal Processing
- Computer Vision and Pattern Recognition
- Information Systems
- Experimental and Cognitive Psychology
- Co-authors
- Giuseppe RiccardiAlessandro MoschittiSilvia QuarteroniSara TonelliChristian RaymondSophie RossetRenato De MoriPatrick Lehnen
- Topics
- Natural Language Processing Techniques (22 papers)Topic Modeling (20 papers)Speech and dialogue systems (12 papers)
- Journals
- IEEE Transactions on Audio Speech and Language ProcessingHAL (Le Centre pour la Communication Scientifique Directe)arXiv (Cornell University)
In The Last Decade
Marco Dinarelli
21 papers receiving 198 citations
Peers
Comparison fields: 5 of 26
- Artificial Intelligence 214
- Signal Processing 27
- Computer Vision and Pattern Recognition 19
- Information Systems 5
- Experimental and Cognitive Psychology 5
Countries citing papers authored by Marco Dinarelli
This map shows the geographic impact of Marco Dinarelli'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 Marco Dinarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Dinarelli more than expected).
Fields of papers citing papers by Marco Dinarelli
This network shows the impact of papers produced by Marco Dinarelli. 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 Marco Dinarelli. The network helps show where Marco Dinarelli may publish in the future.
Co-authorship network of co-authors of Marco Dinarelli
This figure shows the co-authorship network connecting the top 25 collaborators of Marco Dinarelli. A scholar is included among the top collaborators of Marco Dinarelli 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 Marco Dinarelli. Marco Dinarelli 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 | 6 | |
| 3 | 3 | |
| 4 | 34 | |
| 5 | Multi-Task Sequence Prediction For Tunisian Arabizi Multi-Level Annotation | 1 |
| 6 | 7 | |
| 7 | 5 | |
| 8 | Apports des analyses syntaxiques pour la détection automatique de mentions dans un corpus de français oral | 1 |
| 9 | 3 | |
| 10 | LIMSI $@$ WMT13 | 7 |
| 11 | Models Cascade for Tree-Structured Named Entity Detection | 10 |
| 12 | 16 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 6 | |
| 16 | 9 | |
| 17 | 2 | |
| 18 | 8 | |
| 19 | 10 | |
| 20 | 2 |
About Marco Dinarelli
Marco Dinarelli is a scholar working on Artificial Intelligence, Signal Processing and Language and Linguistics, having authored 24 papers that have together received 222 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (22 papers), Topic Modeling (20 papers) and Speech and dialogue systems (12 papers). The work is most often cited by research in Artificial Intelligence (214 citations), Signal Processing (27 citations) and Computer Vision and Pattern Recognition (19 citations). Marco Dinarelli has collaborated with scholars based in France, Italy and Canada. Frequent co-authors include Giuseppe Riccardi, Alessandro Moschitti, Silvia Quarteroni, Sara Tonelli, Christian Raymond, Sophie Rosset, Renato De Mori, Patrick Lehnen, Stefan Hahn and Florence Lefèvre. Their work appears in journals such as IEEE Transactions on Audio Speech and Language Processing, HAL (Le Centre pour la Communication Scientifique Directe) and arXiv (Cornell University).
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.