Antonio Bella
Impact in
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- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Text and Document Classification Technologies
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
Papers in
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- Machine Learning and Data Classification 3
- Imbalanced Data Classification Techniques 2
- Anomaly Detection Techniques and Applications 2
- Multi-Agent Systems and Negotiation 1
- Co-authors
- Marïa José Ramírez-Quintana (5 shared papers)Cèsar Ferri (5 shared papers)José Hernández‐Orallo (5 shared papers)Paola Piscopo (1 shared paper)Giulia Remoli (1 shared paper)Flávia Mayer (1 shared paper)Marco Canevelli (1 shared paper)Ilaria Bacigalupo (1 shared paper)
- Journals
- Applied Intelligence (1 paper)Data Mining and Knowledge Discovery (1 paper)International Journal of Geriatric Psychiatry (1 paper)Computing (1 paper)SSRN Electronic Journal (1 paper)
In The Last Decade
Antonio Bella
5 papers receiving 108 citations
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 82
- Statistics and Probability 6
- Medical Laboratory Technology 1
- General Social Sciences 2
- Management Science and Operations Research 7
Countries citing papers authored by Antonio Bella
This map shows the geographic impact of Antonio Bella'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 Antonio Bella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antonio Bella more than expected).
Fields of papers citing papers by Antonio Bella
This network shows the impact of papers produced by Antonio Bella. 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 Antonio Bella. The network helps show where Antonio Bella may publish in the future.
Co-authors
The 25 scholars most cited alongside Antonio Bella, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 58 | |
| 2 | 2012 | 27 | |
| 3 | 2020 | 16 | |
| 4 | 2013 | 8 | |
| 5 | 2010 | 3 | |
| 6 | 2020 | 0 | |
| 7 | Negotiation with Price-dependent Probability Models. | 2009 | 0 |
About Antonio Bella
Antonio Bella is a scholar working on Artificial Intelligence, Infectious Diseases, Neurology, General Health Professions and Information Systems, having authored 7 papers that have together received 112 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (3 papers), Imbalanced Data Classification Techniques (2 papers), Anomaly Detection Techniques and Applications (2 papers), Data Mining Algorithms and Applications (1 paper), Recommender Systems and Techniques (1 paper), Rough Sets and Fuzzy Logic (1 paper), Multi-Agent Systems and Negotiation (1 paper) and Auction Theory and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (82 citations), Statistics and Probability (6 citations), Medical Laboratory Technology (1 citation), General Social Sciences (2 citations) and Management Science and Operations Research (7 citations). Antonio Bella has collaborated with scholars based in Spain, Italy and Belarus. Frequent co-authors include Marïa José Ramírez-Quintana, Cèsar Ferri, José Hernández‐Orallo, Paola Piscopo, Giulia Remoli, Flávia Mayer, Marco Canevelli, Ilaria Bacigalupo, Patrizio Pezzotti and Eleonora Lacorte. Their work appears in journals such as Applied Intelligence, Data Mining and Knowledge Discovery, International Journal of Geriatric Psychiatry, Computing and SSRN Electronic Journal.
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.