João Bártolo Gomes
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Materials Chemistry
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Co-authors
- Shonali KrishnaswamyHai-Long NguyenMohamed Medhat GaberHong CaoJianneng CaoMin WuFrederic StahlErnestina Menasalvas
- Topics
- Data Stream Mining Techniques (12 papers)Time Series Analysis and Forecasting (9 papers)Anomaly Detection Techniques and Applications (5 papers)
- Journals
- Expert Systems with ApplicationsIEEE Transactions on Neural Networks and Learning SystemsNeurocomputing
- Partner nations
- SingaporeSpainUnited Kingdom
In The Last Decade
João Bártolo Gomes
21 papers receiving 582 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 245
- Electrical and Electronic Engineering 223
- Materials Chemistry 201
- Computer Networks and Communications 108
- Signal Processing 85
Countries citing papers authored by João Bártolo Gomes
This map shows the geographic impact of João Bártolo Gomes'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 João Bártolo Gomes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites João Bártolo Gomes more than expected).
Fields of papers citing papers by João Bártolo Gomes
This network shows the impact of papers produced by João Bártolo Gomes. 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 João Bártolo Gomes. The network helps show where João Bártolo Gomes may publish in the future.
Co-authorship network of co-authors of João Bártolo Gomes
This figure shows the co-authorship network connecting the top 25 collaborators of João Bártolo Gomes. A scholar is included among the top collaborators of João Bártolo Gomes 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 João Bártolo Gomes. João Bártolo Gomes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 50 | |
| 2 | 11 | |
| 3 | 57 | |
| 4 | 1 | |
| 5 | 18 | |
| 6 | 5 | |
| 7 | 217 | |
| 8 | 44 | |
| 9 | 2 | |
| 10 | Recurring concept detection for spam filtering | 3 |
| 11 | 37 | |
| 12 | 25 | |
| 13 | 48 | |
| 14 | 5 | |
| 15 | 17 | |
| 16 | 12 | |
| 17 | 36 | |
| 18 | 6 | |
| 19 | 2 | |
| 20 | 3 |
About João Bártolo Gomes
João Bártolo Gomes is a scholar working on Signal Processing, Transportation and Artificial Intelligence, having authored 21 papers that have together received 603 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (12 papers), Time Series Analysis and Forecasting (9 papers) and Anomaly Detection Techniques and Applications (5 papers). The work is most often cited by research in Transportation (83 citations), Signal Processing (85 citations) and Artificial Intelligence (245 citations). João Bártolo Gomes has collaborated with scholars based in Singapore, Spain and United Kingdom. Frequent co-authors include Shonali Krishnaswamy, Hai-Long Nguyen, Mohamed Medhat Gaber, Hong Cao, Jianneng Cao, Min Wu, Frederic Stahl, Ernestina Menasalvas, Pedro Sousa and Mark Tennant. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.
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.