Ming‐Wei Chang
Impact in
- Artificial Intelligence top 0.01%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Speech and dialogue systems
- Text and Document Classification Technologies
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- Multimodal Machine Learning Applications
Papers in
- Biomaterials 54
- Electrospun Nanofibers in Biomedical Applications 47
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- Topic Modeling 56
- Natural Language Processing Techniques 52
- Co-authors
- Kenton Lee (11 shared papers)Kristina Toutanova (9 shared papers)Jacob Devlin (3 shared papers)Zeeshan Ahmad (86 shared papers)Wen-tau Yih (12 shared papers)Jingsong Li (39 shared papers)Chih‐Jen Lin (6 shared papers)Bing Chen (1 shared paper)
- Journals
- Chemical Engineering Journal (8 papers)Journal of Drug Delivery Science and Technology (8 papers)Pharmaceutics (5 papers)RSC Advances (4 papers)Materials Letters (4 papers)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Ming‐Wei Chang
225 papers receiving 27.6k citations
Ming‐Wei Chang's Hit Papers
Peers
Comparison fields: 5 of 220
- Artificial Intelligence 21.1k
- Computer Vision and Pattern Recognition 5.5k
- Pharmaceutical Science 834
- Biomaterials 1.7k
- Information Systems 3.0k
Countries citing papers authored by Ming‐Wei Chang
This map shows the geographic impact of Ming‐Wei 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 Ming‐Wei Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming‐Wei Chang more than expected).
Fields of papers citing papers by Ming‐Wei Chang
This network shows the impact of papers produced by Ming‐Wei 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 Ming‐Wei Chang. The network helps show where Ming‐Wei Chang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming‐Wei Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 227 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Hit paper breakdown → | 2019 | 19008 |
| 2 | Natural Questions: A Benchmark for Question Answering Research Hit paper breakdown → | 2019 | 1313 |
| 3 | Load Forecasting Using Support Vector Machines: A Study on EUNITE Competition 2001 Hit paper breakdown → | 2004 | 712 |
| 4 | Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base Hit paper breakdown → | 2015 | 542 |
| 5 | A Knowledge-Grounded Neural Conversation Model Hit paper breakdown → | 2018 | 327 |
| 6 | 2016 | 283 | |
| 7 | BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions Hit paper breakdown → | 2019 | 200 |
| 8 | Question Answering Using Enhanced Lexical Semantic Models | 2013 | 169 |
| 9 | Importance of semantic representation: dataless classification | 2008 | 166 |
| 10 | 2015 | 159 | |
| 11 | Retrieval Augmented Language Model Pre-Training | 2020 | 156 |
| 12 | Driving Semantic Parsing from the World's Response | 2010 | 156 |
| 13 | 2018 | 145 | |
| 14 | 2017 | 139 | |
| 15 | Guiding Semi-Supervision with Constraint-Driven Learning | 2007 | 130 |
| 16 | 2016 | 123 | |
| 17 | 2010 | 121 | |
| 18 | To Link or Not to Link? A Study on End-to-End Tweet Entity Linking | 2013 | 114 |
| 19 | 2021 | 113 | |
| 20 | 2010 | 111 |
About Ming‐Wei Chang
Ming‐Wei Chang is a scholar working on Biomaterials, Artificial Intelligence, Pharmaceutical Science, Biomedical Engineering and Electrical and Electronic Engineering, having authored 227 papers that have together received 29.5k indexed citations. Recurring topics across this work include Topic Modeling (56 papers), Natural Language Processing Techniques (52 papers), Electrospun Nanofibers in Biomedical Applications (47 papers), Electrohydrodynamics and Fluid Dynamics (42 papers), Advanced Sensor and Energy Harvesting Materials (18 papers), Multimodal Machine Learning Applications (16 papers), Advanced Drug Delivery Systems (14 papers) and Advancements in Transdermal Drug Delivery (14 papers). The work is most often cited by research in Artificial Intelligence (21.1k citations), Computer Vision and Pattern Recognition (5.5k citations), Pharmaceutical Science (834 citations), Biomaterials (1.7k citations) and Information Systems (3.0k citations). Ming‐Wei Chang has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Kenton Lee, Kristina Toutanova, Jacob Devlin, Zeeshan Ahmad, Wen-tau Yih, Jingsong Li, Chih‐Jen Lin, Bing Chen, Dan Roth and Jianfeng Gao. Their work appears in journals such as Chemical Engineering Journal, Journal of Drug Delivery Science and Technology, Pharmaceutics, RSC Advances and Materials Letters.
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.