Mamoru Komachi
About
In The Last Decade
Mamoru Komachi
116 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 1.1k
- Computer Vision and Pattern Recognition 183
- Information Systems 110
- Language and Linguistics 32
- Molecular Biology 31
Countries citing papers authored by Mamoru Komachi
This map shows the geographic impact of Mamoru Komachi'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 Mamoru Komachi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mamoru Komachi more than expected).
Fields of papers citing papers by Mamoru Komachi
This network shows the impact of papers produced by Mamoru Komachi. 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 Mamoru Komachi. The network helps show where Mamoru Komachi may publish in the future.
Co-authorship network of co-authors of Mamoru Komachi
This figure shows the co-authorship network connecting the top 25 collaborators of Mamoru Komachi. A scholar is included among the top collaborators of Mamoru Komachi 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 Mamoru Komachi. Mamoru Komachi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 13 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | Automated Essay Scoring System for Nonnative Japanese Learners | 3 |
| 9 | TMU Japanese-Chinese Unsupervised NMT System for WAT 2018 Translation Task. | 1 |
| 10 | Japanese Sentiment Classification using a Tree-Structured Long Short-Term Memory with Attention. | 1 |
| 11 | Neural Reordering Model Considering Phrase Translation and Word Alignment for Phrase-based Translation | 5 |
| 12 | Japanese Sentiment Classification with Stacked Denoising Auto-Encoder using Distributed Word Representation | 3 |
| 13 | NAIST at the NLI 2013 Shared Task | 6 |
| 14 | NAIST at 2013 CoNLL Grammatical Error Correction Shared Task | 18 |
| 15 | UniDic for Early Middle Japanese: a Dictionary for Morphological Analysis of Classical Japanese | 4 |
| 16 | Learning of Linear Ordering Problems and its Application to J-E Patent Translation in NTCIR-9 PatentMT | 7 |
| 17 | Japanese Predicate Argument Structure Analysis Exploiting Argument Position and Type | 20 |
| 18 | Narrative Schema as World Knowledge for Coreference Resolution | 9 |
| 19 | Error Correcting Romaji-kana Conversion for Japanese Language Education | 4 |
| 20 | NAIST-NTT System Description f or Patent Translation Task at NTCIR-7 | 0 |
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.