Yi Chang
- Artificial Intelligence top 0.2%
- Topic Modeling 37
- Text and Document Classification Technologies 25
- Advanced Graph Neural Networks 24
- Natural Language Processing Techniques 20
- Information Systems top 0.2%
- Information Retrieval and Search Behavior 45
- Web Data Mining and Analysis 38
- Recommender Systems and Techniques 22
- Health Informatics top 1%
- Signal Processing top 1%
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- Advanced Image and Video Retrieval Techniques 21
- Co-authors
- Chikashi NobataAchint ThomasJoel TetreaultYashar MehdadJiliang TangAnlei DongZhaohui ZhengPhilip S. Yu
- Journals
- IEEE Transactions on Knowledge and Data Engineering (13 papers)IEEE Transactions on Neural Networks and Learning Systems (7 papers)Pattern Recognition (5 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Yi Chang
186 papers receiving 5.4k citations
Hit Papers
Peers
Comparison fields: 5 of 167
- Artificial Intelligence 3.7k
- Information Systems 1.8k
- Health Informatics 97
- Statistical and Nonlinear Physics 576
- Signal Processing 465
Countries citing papers authored by Yi Chang
This map shows the geographic impact of Yi 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 Yi Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Chang more than expected).
Fields of papers citing papers by Yi Chang
This network shows the impact of papers produced by Yi 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 Yi Chang. The network helps show where Yi Chang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yi 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 16 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 36 | |
| 7 | 2023 | 3 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 5 | |
| 10 | 2023 | 4 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 9 | |
| 13 | 2022 | 5 | |
| 14 | 2021 | 17 | |
| 15 | 2021 | 7 | |
| 16 | A Novel Cascade Binary Tagging Framework for Relational Triple Extractionbreakdown → | 2020 | 309 |
| 17 | 2020 | 10 | |
| 18 | 2015 | 11 | |
| 19 | Learning Recurrent Event Queries for Web Search | 2010 | 18 |
| 20 | Search Engine Adaptation by Feedback Control Adjustment for Time-sensitive Query | 2009 | 3 |
About Yi Chang
Yi Chang is a scholar working on Artificial Intelligence, Information Systems and Signal Processing, having authored 201 papers that have together received 5.7k indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (45 papers), Web Data Mining and Analysis (38 papers), Topic Modeling (37 papers), Text and Document Classification Technologies (25 papers), Advanced Graph Neural Networks (24 papers), Recommender Systems and Techniques (22 papers), Advanced Image and Video Retrieval Techniques (21 papers) and Natural Language Processing Techniques (20 papers). The work is most often cited by research in Artificial Intelligence (3.7k citations), Information Systems (1.8k citations) and Health Informatics (97 citations). Yi Chang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Chikashi Nobata, Achint Thomas, Joel Tetreault, Yashar Mehdad, Jiliang Tang, Anlei Dong, Zhaohui Zheng, Philip S. Yu, Huan Liu and Yue Wang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks and Learning Systems, Pattern Recognition, Neurocomputing and ACM Transactions on Intelligent Systems and Technology.
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.