Anísio Lacerda
- Information Systems top 2%
- Artificial Intelligence top 5%
- Management Science and Operations Research top 5%
- Computer Vision and Pattern Recognition top 10%
- Sociology and Political Science
- Co-authors
- Nívio ZivianiAdriano VelosoMarco Túlio RibeiroGisele L. PappaMarcos André GonçalvesMarco CristoWeiguo FanBerthier Ribeiro‐Neto
- Topics
- Recommender Systems and Techniques (18 papers)Advanced Bandit Algorithms Research (13 papers)Advanced Multi-Objective Optimization Algorithms (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaInformation SciencesNeurocomputing
In The Last Decade
Anísio Lacerda
53 papers receiving 634 citations
Peers
Comparison fields: 5 of 74
- Information Systems 351
- Artificial Intelligence 266
- Management Science and Operations Research 176
- Computer Vision and Pattern Recognition 125
- Sociology and Political Science 85
Countries citing papers authored by Anísio Lacerda
This map shows the geographic impact of Anísio Lacerda'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 Anísio Lacerda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anísio Lacerda more than expected).
Fields of papers citing papers by Anísio Lacerda
This network shows the impact of papers produced by Anísio Lacerda. 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 Anísio Lacerda. The network helps show where Anísio Lacerda may publish in the future.
Co-authorship network of co-authors of Anísio Lacerda
This figure shows the co-authorship network connecting the top 25 collaborators of Anísio Lacerda. A scholar is included among the top collaborators of Anísio Lacerda 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 Anísio Lacerda. Anísio Lacerda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 8 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 5 | |
| 12 | 2 | |
| 13 | 4 | |
| 14 | 13 | |
| 15 | 4 | |
| 16 | 7 | |
| 17 | 13 | |
| 18 | 7 | |
| 19 | 4 | |
| 20 | 4 |
About Anísio Lacerda
Anísio Lacerda is a scholar working on Management Science and Operations Research, Information Systems and Artificial Intelligence, having authored 55 papers that have together received 665 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (18 papers), Advanced Bandit Algorithms Research (13 papers) and Advanced Multi-Objective Optimization Algorithms (8 papers). The work is most often cited by research in Information Systems (351 citations), Management Science and Operations Research (176 citations) and Artificial Intelligence (266 citations). Anísio Lacerda has collaborated with scholars based in Brazil, France and Portugal. Frequent co-authors include Nívio Ziviani, Adriano Veloso, Marco Túlio Ribeiro, Gisele L. Pappa, Marcos André Gonçalves, Marco Cristo, Weiguo Fan, Berthier Ribeiro‐Neto, Edleno Silva de Moura and Gabriel P. Oliveira. Their work appears in journals such as SHILAP Revista de lepidopterología, Information Sciences 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.