Kiyoshi Sudo
Impact in
- Artificial Intelligence top 5%
- Natural Language Processing Techniques
- Topic Modeling
- Advanced Text Analysis Techniques
- Semantic Web and Ontologies
- Text and Document Classification Technologies
- Speech and dialogue systems
- Text Readability and Simplification
- Information Systems top 10%
- Web Data Mining and Analysis
Papers in
-
- Semantic Web and Ontologies 7
- Natural Language Processing Techniques 5
- Topic Modeling 4
- Advanced Text Analysis Techniques 1
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- Advanced Database Systems and Queries 3
- Co-authors
- Satoshi Sekine (10 shared papers)Chikashi Nobata (2 shared papers)Ralph Grishman (5 shared papers)Yusuke Shinyama (2 shared papers)Kiyotaka Uchimoto (2 shared papers)Hitoshi Isahara (2 shared papers)Masaki Murata (1 shared paper)Yujie Zhang (1 shared paper)
- Journals
- Language Resources and Evaluation (1 paper)NTCIR (1 paper)
- Partner nations
- United StatesBermudaJapan
In The Last Decade
Kiyoshi Sudo
11 papers receiving 333 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 377
- Information Systems 90
- Communication 16
- Geography, Planning and Development 10
- Signal Processing 13
Countries citing papers authored by Kiyoshi Sudo
This map shows the geographic impact of Kiyoshi Sudo'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 Kiyoshi Sudo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kiyoshi Sudo more than expected).
Fields of papers citing papers by Kiyoshi Sudo
This network shows the impact of papers produced by Kiyoshi Sudo. 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 Kiyoshi Sudo. The network helps show where Kiyoshi Sudo may publish in the future.
Co-authors
The 11 scholars most cited alongside Kiyoshi Sudo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Extended Named Entity Hierarchy | 2002 | 130 |
| 2 | 2002 | 120 | |
| 3 | 2003 | 79 | |
| 4 | 2001 | 30 | |
| 5 | 2004 | 14 | |
| 6 | 2004 | 10 | |
| 7 | Statistical Matching of Two Ontologies | 1999 | 5 |
| 8 | NYU/CRL QA System, QAC Question Analysis and CRL QA Data. | 2002 | 3 |
| 9 | Unsupervised discovery of extraction patterns for information extraction | 2004 | 3 |
| 10 | 2003 | 2 | |
| 11 | 2005 | 1 |
About Kiyoshi Sudo
Kiyoshi Sudo is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Management Science and Operations Research and Signal Processing, having authored 11 papers that have together received 397 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (7 papers), Natural Language Processing Techniques (5 papers), Topic Modeling (4 papers), Advanced Database Systems and Queries (3 papers), Data Quality and Management (2 papers), Advanced Text Analysis Techniques (1 paper), SAS software applications and methods (1 paper) and Spam and Phishing Detection (1 paper). The work is most often cited by research in Artificial Intelligence (377 citations), Information Systems (90 citations), Communication (16 citations), Geography, Planning and Development (10 citations) and Signal Processing (13 citations). Kiyoshi Sudo has collaborated with scholars based in United States, Bermuda and Japan. Frequent co-authors include Satoshi Sekine, Chikashi Nobata, Ralph Grishman, Yusuke Shinyama, Kiyotaka Uchimoto, Hitoshi Isahara, Masaki Murata, Yujie Zhang, Amit Bagga and John Bentley. Their work appears in journals such as Language Resources and Evaluation and NTCIR.
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.