Naoki Abe
Impact in
- Artificial Intelligence top 0.5%
- Machine Learning and Algorithms
- Imbalanced Data Classification Techniques
- Anomaly Detection Techniques and Applications
- Machine Learning and Data Classification
- Natural Language Processing Techniques
- Topic Modeling
- Algorithms and Data Compression
- Computational Mathematics top 10%
Papers in
-
- Machine Learning and Algorithms 20
- Algorithms and Data Compression 13
- Natural Language Processing Techniques 11
- Imbalanced Data Classification Techniques 8
- Machine Learning and Data Classification 7
- Topic Modeling 5
- Co-authors
- Bianca Zadrozny (8 shared papers)John Langford (3 shared papers)Hiroshi Mamitsuka (8 shared papers)Hang Li (7 shared papers)Aurélie Lozano (9 shared papers)Yan Liu (3 shared papers)Atsuyoshi Nakamura (8 shared papers)Manfred K. Warmuth (4 shared papers)
- Journals
- Machine Learning (3 papers)Modern Rheumatology (3 papers)Journal of Gastroenterology and Hepatology (2 papers)Computational Linguistics (2 papers)Computer Networks (2 papers)
- Partner nations
- JapanUnited StatesBrazil
In The Last Decade
Naoki Abe
96 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 154
- Artificial Intelligence 1.8k
- Computational Mathematics 16
- Management Science and Operations Research 288
- Signal Processing 211
- Statistics and Probability 141
Countries citing papers authored by Naoki Abe
This map shows the geographic impact of Naoki Abe'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 Naoki Abe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naoki Abe more than expected).
Fields of papers citing papers by Naoki Abe
This network shows the impact of papers produced by Naoki Abe. 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 Naoki Abe. The network helps show where Naoki Abe may publish in the future.
Co-authors
The 25 scholars most cited alongside Naoki Abe, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 466 | |
| 2 | Query Learning Strategies Using Boosting and Bagging | 1998 | 231 |
| 3 | 2006 | 214 | |
| 4 | 2007 | 179 | |
| 5 | 1995 | 121 | |
| 6 | 2009 | 110 | |
| 7 | 2004 | 96 | |
| 8 | 1990 | 93 | |
| 9 | 2006 | 92 | |
| 10 | 2003 | 88 | |
| 11 | Collaborative Filtering Using Weighted Majority Prediction Algorithms | 1998 | 85 |
| 12 | 1999 | 70 | |
| 13 | Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction | 2009 | 63 |
| 14 | 2009 | 63 | |
| 15 | 1992 | 50 | |
| 16 | 2002 | 48 | |
| 17 | 2010 | 46 | |
| 18 | 2009 | 44 | |
| 19 | 2003 | 39 | |
| 20 | 1998 | 38 |
About Naoki Abe
Naoki Abe is a scholar working on Artificial Intelligence, Molecular Biology, Management Science and Operations Research, Information Systems and Computational Theory and Mathematics, having authored 103 papers that have together received 2.9k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (20 papers), Algorithms and Data Compression (13 papers), Natural Language Processing Techniques (11 papers), Data Mining Algorithms and Applications (9 papers), Consumer Market Behavior and Pricing (9 papers), Imbalanced Data Classification Techniques (8 papers), Machine Learning and Data Classification (7 papers) and Topic Modeling (5 papers). The work is most often cited by research in Artificial Intelligence (1.8k citations), Computational Mathematics (16 citations), Management Science and Operations Research (288 citations), Signal Processing (211 citations) and Statistics and Probability (141 citations). Naoki Abe has collaborated with scholars based in Japan, United States and Brazil. Frequent co-authors include Bianca Zadrozny, John Langford, Hiroshi Mamitsuka, Hang Li, Aurélie Lozano, Yan Liu, Atsuyoshi Nakamura, Manfred K. Warmuth, Andrew O. Arnold and Hisashi Kashima. Their work appears in journals such as Machine Learning, Modern Rheumatology, Journal of Gastroenterology and Hepatology, Computational Linguistics and Computer Networks.
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.