Yee Seng Chan
- Artificial Intelligence top 1%
- Molecular Biology
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Materials Chemistry
- Co-authors
- Hwee Tou NgDan RothDavid ChiangQuang DoBin WangHironobu HayashiSteve DeNeefeHiroko Yamada
- Topics
- Topic Modeling (17 papers)Natural Language Processing Techniques (17 papers)Speech and dialogue systems (5 papers)
- Partner nations
- SingaporeUnited StatesJapan
In The Last Decade
Yee Seng Chan
22 papers receiving 950 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 945
- Molecular Biology 81
- Information Systems 66
- Computer Vision and Pattern Recognition 51
- Materials Chemistry 50
Countries citing papers authored by Yee Seng Chan
This map shows the geographic impact of Yee Seng Chan'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 Yee Seng Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yee Seng Chan more than expected).
Fields of papers citing papers by Yee Seng Chan
This network shows the impact of papers produced by Yee Seng Chan. 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 Yee Seng Chan. The network helps show where Yee Seng Chan may publish in the future.
Co-authorship network of co-authors of Yee Seng Chan
This figure shows the co-authorship network connecting the top 25 collaborators of Yee Seng Chan. A scholar is included among the top collaborators of Yee Seng Chan 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 Yee Seng Chan. Yee Seng Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 33 | |
| 3 | 31 | |
| 4 | Towards Few-Shot Event Mention Retrieval: An Evaluation Framework and A Siamese Network Approach | 2 |
| 5 | 1 | |
| 6 | Minimally Supervised Event Causality Identification | 109 |
| 7 | Exploiting Syntactico-Semantic Structures for Relation Extraction | 130 |
| 8 | Exploiting Background Knowledge for Relation Extraction | 52 |
| 9 | 3 | |
| 10 | MAXSIM: A Maximum Similarity Metric for Machine Translation Evaluation | 60 |
| 11 | 37 | |
| 12 | 19 | |
| 13 | Word Sense Disambiguation Improves Statistical Machine Translation | 196 |
| 14 | Domain Adaptation with Active Learning for Word Sense Disambiguation | 81 |
| 15 | 8 | |
| 16 | 38 | |
| 17 | 5 | |
| 18 | Word sense disambiguation with distribution estimation | 40 |
| 19 | 38 | |
| 20 | 92 |
About Yee Seng Chan
Yee Seng Chan is a scholar working on Artificial Intelligence, Human-Computer Interaction and Management Science and Operations Research, having authored 23 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Natural Language Processing Techniques (17 papers) and Speech and dialogue systems (5 papers). The work is most often cited by research in Artificial Intelligence (945 citations), Management Science and Operations Research (43 citations) and Information Systems (66 citations). Yee Seng Chan has collaborated with scholars based in Singapore, United States and Japan. Frequent co-authors include Hwee Tou Ng, Dan Roth, David Chiang, Quang Do, Bin Wang, Hironobu Hayashi, Steve DeNeefe, Hiroko Yamada, Naoki Aratani and Yusuke Tsutsui. Their work appears in journals such as Nature Communications, Chemistry - A European Journal and European Journal of Organic Chemistry.
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.