Tapio Elomaa
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computational Theory and Mathematics top 5%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Co-authors
- Juho RousuMatti KääriäinenHeikki MannilaHannu ToivonenTimo AhoBernard ŽenkoSašo DžeroskiJaakko Hollmén
- Topics
- Machine Learning and Algorithms (8 papers)Machine Learning and Data Classification (8 papers)Data Mining Algorithms and Applications (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaPattern RecognitionMachine Learning
- Partner nations
- FinlandUnited StatesSlovenia
In The Last Decade
Tapio Elomaa
33 papers receiving 509 citations
Peers
Comparison fields: 5 of 93
- Artificial Intelligence 375
- Information Systems 150
- Computational Theory and Mathematics 110
- Computer Vision and Pattern Recognition 97
- Signal Processing 73
Countries citing papers authored by Tapio Elomaa
This map shows the geographic impact of Tapio Elomaa'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 Tapio Elomaa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tapio Elomaa more than expected).
Fields of papers citing papers by Tapio Elomaa
This network shows the impact of papers produced by Tapio Elomaa. 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 Tapio Elomaa. The network helps show where Tapio Elomaa may publish in the future.
Co-authorship network of co-authors of Tapio Elomaa
This figure shows the co-authorship network connecting the top 25 collaborators of Tapio Elomaa. A scholar is included among the top collaborators of Tapio Elomaa 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 Tapio Elomaa. Tapio Elomaa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | FEASIBILITY OF B2C CUSTOMER RELATIONSHIP ANALYTICS IN THE B2B INDUSTRIAL CONTEXT | 4 |
| 2 | 13 | |
| 3 | 7 | |
| 4 | 3 | |
| 5 | Multi-target regression with rule ensembles | 73 |
| 6 | 4 | |
| 7 | Poketree: A Dynamically Competitive Data Structure with Good Worst-Case Performance | 1 |
| 8 | 1 | |
| 9 | Selective Rademacher Penalization and Reduced Error Pruning of Decision Trees | 16 |
| 10 | 19 | |
| 11 | Fast Minimum Training Error Discretization | 4 |
| 12 | 7 | |
| 13 | Fast minimum error discretization | 2 |
| 14 | 0 | |
| 15 | 0 | |
| 16 | Proceedings of the 13th European Conference on Machine Learning | 17 |
| 17 | On the Computational Complexity of Optimal Multisplitting | 8 |
| 18 | Robot Landmark Learning with SVMs | 1 |
| 19 | Generalizing Boundary Points | 6 |
| 20 | On the well-behavedness of important attribute evaluation functions | 6 |
About Tapio Elomaa
Tapio Elomaa is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems, having authored 39 papers that have together received 564 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (8 papers), Machine Learning and Data Classification (8 papers) and Data Mining Algorithms and Applications (8 papers). The work is most often cited by research in Artificial Intelligence (375 citations), Computational Theory and Mathematics (110 citations) and Signal Processing (73 citations). Tapio Elomaa has collaborated with scholars based in Finland, United States and Slovenia. Frequent co-authors include Juho Rousu, Matti Kääriäinen, Heikki Mannila, Hannu Toivonen, Timo Aho, Bernard Ženko, Sašo Džeroski, Jaakko Hollmén, Teemu Laine and Petri Suomala. Their work appears in journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Machine Learning.
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.