Isao Goto
- Artificial Intelligence top 5%
- Natural Language Processing Techniques 29
- Topic Modeling 25
- Text Readability and Simplification 8
- Speech and dialogue systems 2
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- Handwritten Text Recognition Techniques 5
- Multimodal Machine Learning Applications 2
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- Translation Studies and Practices 4
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- Biomedical Text Mining and Ontologies 3
- Co-authors
- Eiichiro SumitaBenjamin K. TsouBin LuMasao UtiyamaSadao KurohashiHideki TanakaToshiaki NakazawaChenchen Ding
In The Last Decade
Isao Goto
28 papers receiving 318 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 350
- Computer Vision and Pattern Recognition 101
- Language and Linguistics 19
- Information Systems 24
- Management of Technology and Innovation 6
Countries citing papers authored by Isao Goto
This map shows the geographic impact of Isao Goto'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 Isao Goto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isao Goto more than expected).
Fields of papers citing papers by Isao Goto
This network shows the impact of papers produced by Isao Goto. 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 Isao Goto. The network helps show where Isao Goto may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Isao Goto, 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 | 2022 | 0 | |
| 2 | Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT. | 2020 | 4 |
| 3 | 2020 | 0 | |
| 4 | 2020 | 14 | |
| 5 | 2020 | 0 | |
| 6 | Overview of the 7th Workshop on Asian Translation. | 2020 | 3 |
| 7 | 2019 | 1 | |
| 8 | 2019 | 27 | |
| 9 | 2018 | 19 | |
| 10 | 2017 | 8 | |
| 11 | 2015 | 11 | |
| 12 | Japanese news simplification: tak design, data set construction, and analysis of simplified text | 2015 | 1 |
| 13 | 2015 | 0 | |
| 14 | Distortion Model Considering Rich Context for Statistical Machine Translation | 2013 | 5 |
| 15 | 2013 | 20 | |
| 16 | Post-ordering by Parsing for Japanese-English Statistical Machine Translation | 2012 | 19 |
| 17 | Overview of the patent machine translation task at the NTCIR-9 workshop | 2011 | 119 |
| 18 | A Comparison Study of Parsers for Patent Machine Translation. | 2011 | 2 |
| 19 | 2010 | 1 | |
| 20 | 2001 | 7 |
About Isao Goto
Isao Goto is a scholar working on Artificial Intelligence, Language and Linguistics and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 376 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (29 papers), Topic Modeling (25 papers), Text Readability and Simplification (8 papers), Handwritten Text Recognition Techniques (5 papers), Translation Studies and Practices (4 papers), Biomedical Text Mining and Ontologies (3 papers), Speech and dialogue systems (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Artificial Intelligence (350 citations), Computer Vision and Pattern Recognition (101 citations) and Language and Linguistics (19 citations). Isao Goto has collaborated with scholars based in Japan, China and Czechia. Frequent co-authors include Eiichiro Sumita, Benjamin K. Tsou, Bin Lu, Masao Utiyama, Sadao Kurohashi, Hideki Tanaka, Toshiaki Nakazawa, Chenchen Ding, Raj Dabre and Win Pa Pa. Their work appears in journals such as Language Resources and Evaluation, ACM Transactions on Asian Language Information Processing and ACM Transactions on Asian and Low-Resource Language Information Processing.
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.