Bart Baesens
About
In The Last Decade
Bart Baesens
252 papers receiving 11.4k citations
Hit Papers
Peers
Comparison fields: 5 of 188
- Artificial Intelligence 5.3k
- Information Systems 3.7k
- Accounting 3.1k
- Marketing 2.0k
- Management Information Systems 1.8k
Countries citing papers authored by Bart Baesens
This map shows the geographic impact of Bart Baesens'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 Bart Baesens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bart Baesens more than expected).
Fields of papers citing papers by Bart Baesens
This network shows the impact of papers produced by Bart Baesens. 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 Bart Baesens. The network helps show where Bart Baesens may publish in the future.
Co-authorship network of co-authors of Bart Baesens
This figure shows the co-authorship network connecting the top 25 collaborators of Bart Baesens. A scholar is included among the top collaborators of Bart Baesens 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 Bart Baesens. Bart Baesens is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 10 | |
| 4 | 3 | |
| 5 | 61 | |
| 6 | 1 | |
| 7 | 84 | |
| 8 | 40 | |
| 9 | Improving Resampling-based Ensemble in Churn Prediction | 3 |
| 10 | 78 | |
| 11 | 38 | |
| 12 | The use of data quality information (DQI) for decision-making: an exploratory study | 1 |
| 13 | Using social network classifiers for predicting e-commerce adoption | 1 |
| 14 | Software defect prediction based on association rule classification | 4 |
| 15 | Benchmarking state-of-the-art regression algorithms for loss given default modelling | 1 |
| 16 | Placing process intelligence within the business intelligence framework | 3 |
| 17 | Risk management and regulatory compliance: a data mining framework based on neural network rule extraction | 10 |
| 18 | Web usage mining: a practical study | 6 |
| 19 | A support vector machine approach to credit scoring | 79 |
| 20 | Sensitivity based pruning of input variables by means of weight cascaded retraining | 1 |
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.