Jing-Shin Chang
- Artificial Intelligence top 5%
- Molecular Biology
- Information Systems
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Topics
- Natural Language Processing Techniques (22 papers)Topic Modeling (14 papers)Biomedical Text Mining and Ontologies (5 papers)
- Journals
- Machine TranslationMeeting of the Association for Computational LinguisticsComputers and the Humanities
- Partner nations
- Taiwan
In The Last Decade
Jing-Shin Chang
25 papers receiving 274 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 325
- Molecular Biology 41
- Information Systems 39
- Computer Vision and Pattern Recognition 27
- Computational Theory and Mathematics 25
Countries citing papers authored by Jing-Shin Chang
This map shows the geographic impact of Jing-Shin Chang'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 Jing-Shin Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing-Shin Chang more than expected).
Fields of papers citing papers by Jing-Shin Chang
This network shows the impact of papers produced by Jing-Shin Chang. 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 Jing-Shin Chang. The network helps show where Jing-Shin Chang may publish in the future.
Co-authorship network of co-authors of Jing-Shin Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Jing-Shin Chang. A scholar is included among the top collaborators of Jing-Shin Chang 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 Jing-Shin Chang. Jing-Shin Chang 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 | Translating Common English and Chinese Verb-Noun Pairs in Technical Documents with Collocational and Bilingual Information | 1 |
| 3 | An EM Algorithm for Context-Based Searching and Disambiguation with Application to Synonym Term Alignment | 3 |
| 4 | 7 | |
| 5 | Mining Atomic Chinese Abbreviation Pairs: A Probabilistic Model for Single Character Word Recovery | 7 |
| 6 | A Preliminary Study on Probabilistic Models for Chinese Abbreviations | 14 |
| 7 | A customizable, self-learning parameterized MT system: the next generation | 2 |
| 8 | A Multivariate Gaussian Mixture Model for Automatic Compound Word Extraction | 4 |
| 9 | Corpus-Based Statistics-Oriented (CBSO) Machine Translation Researches in Taiwan | 1 |
| 10 | 47 | |
| 11 | 9 | |
| 12 | Automatic Construction of a Chinese Electronic Dictionary. | 11 |
| 13 | 10 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 25 | |
| 17 | 62 | |
| 18 | ArchTran: A Corpus-based Statistics-oriented English-Chinese Machine Translation System | 15 |
| 19 | A Sequential Truncation Parsing Algorithm Based on the Score Function | 6 |
| 20 | 8 |
About Jing-Shin Chang
Jing-Shin Chang is a scholar working on Artificial Intelligence, Language and Linguistics and Signal Processing, having authored 27 papers that have together received 350 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (22 papers), Topic Modeling (14 papers) and Biomedical Text Mining and Ontologies (5 papers). The work is most often cited by research in Artificial Intelligence (325 citations), Language and Linguistics (19 citations) and Information Systems (39 citations). Jing-Shin Chang has collaborated with scholars based in Taiwan. Frequent co-authors include Keh‐Yih Su, Yi‐Chung Lin, Shu‐Chuan Chen, Chao-Lin Liu and Mei-Hui Su. Their work appears in journals such as Machine Translation, Meeting of the Association for Computational Linguistics and Computers and the Humanities.
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.