Yukihiro Tagami
- Artificial Intelligence top 5%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research
- Computer Networks and Communications
- Co-authors
- Akira TajimaShingo OnoKoji TsukamotoHayato KobayashiNobuyuki ShimizuTaiji SuzukiYuki YanoTomoya Yamazaki
- Topics
- Web Data Mining and Analysis (9 papers)Text and Document Classification Technologies (5 papers)Recommender Systems and Techniques (4 papers)
- Journals
- IEICE Transactions on Information and SystemsKnowledge Discovery and Data MiningNeural Information Processing Systems
- Partner nations
- JapanUnited Kingdom
In The Last Decade
Yukihiro Tagami
12 papers receiving 383 citations
Hit Papers
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 309
- Information Systems 308
- Computer Vision and Pattern Recognition 110
- Management Science and Operations Research 38
- Computer Networks and Communications 35
Countries citing papers authored by Yukihiro Tagami
This map shows the geographic impact of Yukihiro Tagami'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 Yukihiro Tagami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yukihiro Tagami more than expected).
Fields of papers citing papers by Yukihiro Tagami
This network shows the impact of papers produced by Yukihiro Tagami. 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 Yukihiro Tagami. The network helps show where Yukihiro Tagami may publish in the future.
Co-authorship network of co-authors of Yukihiro Tagami
This figure shows the co-authorship network connecting the top 25 collaborators of Yukihiro Tagami. A scholar is included among the top collaborators of Yukihiro Tagami 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 Yukihiro Tagami. Yukihiro Tagami is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Scalable and Plug-in Based System to Construct A Production-Level Knowledge Base. | 0 |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | Embedding-based News Recommendation for Millions of Usersbreakdown → | 284 |
| 6 | 77 | |
| 7 | 4 | |
| 8 | Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning | 2 |
| 9 | 2 | |
| 10 | 4 | |
| 11 | Gaussian process nonparametric tensor estimator and its minimax optimality | 9 |
| 12 | 6 | |
| 13 | 1 | |
| 14 | 0 | |
| 15 | 26 |
About Yukihiro Tagami
Yukihiro Tagami is a scholar working on Computational Mathematics, Information Systems and Artificial Intelligence, having authored 15 papers that have together received 418 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (9 papers), Text and Document Classification Technologies (5 papers) and Recommender Systems and Techniques (4 papers). The work is most often cited by research in Computational Mathematics (14 citations), Information Systems (308 citations) and Artificial Intelligence (309 citations). Yukihiro Tagami has collaborated with scholars based in Japan and United Kingdom. Frequent co-authors include Akira Tajima, Shingo Ono, Koji Tsukamoto, Hayato Kobayashi, Nobuyuki Shimizu, Taiji Suzuki, Yuki Yano, Tomoya Yamazaki and Yusuke Tanaka. Their work appears in journals such as IEICE Transactions on Information and Systems, Knowledge Discovery and Data Mining and Neural Information Processing Systems.
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.