Hajime Tsukada
About
In The Last Decade
Hajime Tsukada
44 papers receiving 608 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 747
- Computer Vision and Pattern Recognition 137
- Molecular Biology 38
- Information Systems 32
- Signal Processing 15
Countries citing papers authored by Hajime Tsukada
This map shows the geographic impact of Hajime Tsukada'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 Hajime Tsukada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hajime Tsukada more than expected).
Fields of papers citing papers by Hajime Tsukada
This network shows the impact of papers produced by Hajime Tsukada. 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 Hajime Tsukada. The network helps show where Hajime Tsukada may publish in the future.
Co-authorship network of co-authors of Hajime Tsukada
This figure shows the co-authorship network connecting the top 25 collaborators of Hajime Tsukada. A scholar is included among the top collaborators of Hajime Tsukada 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 Hajime Tsukada. Hajime Tsukada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | The NAIST-NTT TED talk treebank. | 5 |
| 2 | A Comparative Study of Target Dependency Structures for Statistical Machine Translation | 2 |
| 3 | Learning to Translate with Multiple Objectives | 15 |
| 4 | Learning of Linear Ordering Problems and its Application to J-E Patent Translation in NTCIR-9 PatentMT | 7 |
| 5 | Generalized Minimum Bayes Risk System Combination | 14 |
| 6 | NTT-UT Statistical Machine Translation in NTCIR-9 PatentMT | 16 |
| 7 | Automatic Evaluation of Translation Quality for Distant Language Pairs | 190 |
| 8 | Head Finalization: A Simple Reordering Rule for SOV Languages | 59 |
| 9 | Hierarchical Phrase-based Machine Translation with Word-based Reordering Model | 7 |
| 10 | N-Best Reranking by Multitask Learning | 11 |
| 11 | Divide and Translate: Improving Long Distance Reordering in Statistical Machine Translation | 23 |
| 12 | Analysis of translation model adaptation in statistical machine translation. | 11 |
| 13 | 4 | |
| 14 | Structural Support Vector Machines for Log-Linear Approach in Statistical Machine Translation | 4 |
| 15 | Larger Feature Set Approach for Machine Translation in IWSLT 2007 | 1 |
| 16 | Online Large-Margin Training for Statistical Machine Translation | 127 |
| 17 | NTT statistical machine translation for IWSLT 2006. | 12 |
| 18 | The NTT Statistical Machine Translation System for IWSLT2005 | 4 |
| 19 | NTT's Japanese-English Cross-Language Question Answering System | 5 |
| 20 | Efficient Decoding for Statistical Machine Translation with a Fully Expanded WFST Model. | 6 |
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.