Fernando Bação

79 papers receiving 4.4k citations

Fernando Bação's Hit Papers

What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period? 2020 · 346 citations
3460+3+6Years since publication250500750

Peers

Fernando Bação
Comparison fields: 5 of 173
  • Information Systems and Management 561
  • Computer Science Applications 301
  • Artificial Intelligence 1.6k
  • Media Technology 397
  • Health Information Management 187
Replace Ramesh Sharda with:
Ramesh Sharda United States
Fosca Giannotti Italy
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Soumya K. Ghosh India
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Citations per year

Countries citing papers authored by Fernando Bação

Since Specialization
Citations

This map shows the geographic impact of Fernando Bação'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 Fernando Bação with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Bação more than expected).

Fields of papers citing papers by Fernando Bação

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Bação. 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 Fernando Bação. The network helps show where Fernando Bação may publish in the future.

Co-authors

The 25 scholars most cited alongside Fernando Bação, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fernando Bação Line = papers co-authored together Fernando Bação links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE
Hit paper breakdown →
2018833
2
Effective data generation for imbalanced learning using conditional generative adversarial networks
Hit paper breakdown →
2017424
3
What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period?
Hit paper breakdown →
2020346
4 2009290
5
Gamification: A key determinant of massive open online course (MOOC) success
Hit paper breakdown →
2018234
6 2016226
7 2019199
8
An e-Learning Theoretical Framework.
2016183
9 2012159
10 2015151
11 2017147
12 2016136
13 2021133
14 201695
15 200486
16 201974
17 201869
18 201066
19 202365
20 200750

About Fernando Bação

Fernando Bação is a scholar working on Artificial Intelligence, Information Systems, Media Technology, Sociology and Political Science and Computer Vision and Pattern Recognition, having authored 85 papers that have together received 4.6k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (20 papers), Remote-Sensing Image Classification (8 papers), Machine Learning and Data Classification (8 papers), Data Management and Algorithms (7 papers), Technology Adoption and User Behaviour (7 papers), Geographic Information Systems Studies (6 papers), Online Learning and Analytics (6 papers) and Online and Blended Learning (5 papers). The work is most often cited by research in Information Systems and Management (561 citations), Computer Science Applications (301 citations), Artificial Intelligence (1.6k citations), Media Technology (397 citations) and Health Information Management (187 citations). Fernando Bação has collaborated with scholars based in Portugal, Canada and Brazil. Frequent co-authors include Georgios Douzas, Tiago Oliveira, Felix Last, Manuela Aparício, Yuyang Zhao, Frederico Cruz‐Jesus, Marco Paìnho, Francisco Moreira, Filipe X. Catry and Francisco Rego. Their work appears in journals such as Expert Systems with Applications, Remote Sensing, Information & Management, PLoS ONE and Information Sciences.

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.

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