Paulo Nováis
Impact in
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- Context-Aware Activity Recognition Systems
- Advanced Neural Network Applications
- Artificial Intelligence top 2%
- Multi-Agent Systems and Negotiation
- Semantic Web and Ontologies
Papers in
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- Multi-Agent Systems and Negotiation 37
- Semantic Web and Ontologies 19
- Logic, Reasoning, and Knowledge 17
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- Context-Aware Activity Recognition Systems 41
- Co-authors
- José Neves (65 shared papers)Davide Carneiro (45 shared papers)Ângelo Costa (33 shared papers)Goreti Marreiros (31 shared papers)João Carneiro (24 shared papers)Antonio Fernández‐Caballero (9 shared papers)Vicente Julián (22 shared papers)José Carlos Castillo (4 shared papers)
In The Last Decade
Paulo Nováis
249 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 152
- Computer Vision and Pattern Recognition 470
- Artificial Intelligence 709
- Computer Science Applications 105
- Experimental and Cognitive Psychology 191
- Automotive Engineering 178
Countries citing papers authored by Paulo Nováis
This map shows the geographic impact of Paulo Nováis'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 Paulo Nováis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paulo Nováis more than expected).
Fields of papers citing papers by Paulo Nováis
This network shows the impact of papers produced by Paulo Nováis. 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 Paulo Nováis. The network helps show where Paulo Nováis may publish in the future.
Co-authors
The 25 scholars most cited alongside Paulo Nováis, 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 269 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 173 | |
| 2 | 2012 | 71 | |
| 3 | 2019 | 61 | |
| 4 | 2023 | 61 | |
| 5 | 2012 | 60 | |
| 6 | 2014 | 55 | |
| 7 | 2018 | 52 | |
| 8 | 2018 | 47 | |
| 9 | 2013 | 44 | |
| 10 | 2013 | 44 | |
| 11 | 2017 | 43 | |
| 12 | 2012 | 39 | |
| 13 | 2015 | 39 | |
| 14 | 2018 | 39 | |
| 15 | 2019 | 34 | |
| 16 | 2019 | 32 | |
| 17 | 2021 | 32 | |
| 18 | 2021 | 29 | |
| 19 | 2014 | 28 | |
| 20 | 2023 | 27 |
About Paulo Nováis
Paulo Nováis is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Social Psychology, Information Systems and Computer Networks and Communications, having authored 269 papers that have together received 2.4k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (41 papers), Multi-Agent Systems and Negotiation (37 papers), Semantic Web and Ontologies (19 papers), Logic, Reasoning, and Knowledge (17 papers), Emotion and Mood Recognition (17 papers), IoT and Edge/Fog Computing (11 papers), Biomedical Text Mining and Ontologies (11 papers) and Artificial Intelligence in Law (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (470 citations), Artificial Intelligence (709 citations), Computer Science Applications (105 citations), Experimental and Cognitive Psychology (191 citations) and Automotive Engineering (178 citations). Paulo Nováis has collaborated with scholars based in Portugal, Spain and Brazil. Frequent co-authors include José Neves, Davide Carneiro, Ângelo Costa, Goreti Marreiros, João Carneiro, Antonio Fernández‐Caballero, Vicente Julián, José Carlos Castillo, José Machado and Francisco Andrade. Their work appears in journals such as Neurocomputing, Electronics, Sensors, Expert Systems with Applications and Logic Journal of IGPL.
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.