Jiang Bian
Impact in
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- Mobile Crowdsensing and Crowdsourcing
- Information Systems top 1%
- Expert finding and Q&A systems
- Recommender Systems and Techniques
- Information Retrieval and Search Behavior
Papers in
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- Topic Modeling 12
- Text and Document Classification Technologies 6
- Domain Adaptation and Few-Shot Learning 6
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- Advanced Image and Video Retrieval Techniques 8
- Advanced Neural Network Applications 7
- Co-authors
- Eugene Agichtein (4 shared papers)Yandong Liu (4 shared papers)Hongyuan Zha (6 shared papers)Haoyi Xiong (33 shared papers)Ding Zhou (2 shared papers)Dejing Dou (8 shared papers)Xuhong Li (5 shared papers)Ji Liu (1 shared paper)
- Journals
- ACM Transactions on Knowledge Discovery from Data (3 papers)IEEE Transactions on Services Computing (2 papers)Machine Learning (2 papers)IEEE Transactions on Multimedia (2 papers)IEEE Transactions on Emerging Topics in Computational Intelligence (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jiang Bian
75 papers receiving 1.5k citations
Jiang Bian's Hit Papers
Peers
Comparison fields: 5 of 140
- Computer Science Applications 326
- Information Systems 700
- Artificial Intelligence 934
- Communication 84
- Health Informatics 16
Countries citing papers authored by Jiang Bian
This map shows the geographic impact of Jiang Bian'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 Jiang Bian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiang Bian more than expected).
Fields of papers citing papers by Jiang Bian
This network shows the impact of papers produced by Jiang Bian. 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 Jiang Bian. The network helps show where Jiang Bian may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiang Bian, 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 78 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond Hit paper breakdown → | 2022 | 246 |
| 2 | 2008 | 199 | |
| 3 | 2008 | 183 | |
| 4 | 2009 | 129 | |
| 5 | 2008 | 109 | |
| 6 | 2019 | 86 | |
| 7 | A Probabilistic Model for Learning Multi-Prototype Word Embeddings | 2014 | 68 |
| 8 | 2022 | 57 | |
| 9 | 2022 | 50 | |
| 10 | Co-learning of Word Representations and Morpheme Representations | 2014 | 44 |
| 11 | 2009 | 41 | |
| 12 | 2010 | 26 | |
| 13 | 2004 | 26 | |
| 14 | 2023 | 18 | |
| 15 | 2017 | 17 | |
| 16 | 2012 | 17 | |
| 17 | 2010 | 16 | |
| 18 | 2019 | 14 | |
| 19 | 2019 | 13 | |
| 20 | 2018 | 12 |
About Jiang Bian
Jiang Bian is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 78 papers that have together received 1.6k indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Recommender Systems and Techniques (8 papers), Expert finding and Q&A systems (8 papers), Advanced Image and Video Retrieval Techniques (8 papers), Advanced Neural Network Applications (7 papers), Text and Document Classification Technologies (6 papers), Mobile Crowdsensing and Crowdsourcing (6 papers) and Domain Adaptation and Few-Shot Learning (6 papers). The work is most often cited by research in Computer Science Applications (326 citations), Information Systems (700 citations), Artificial Intelligence (934 citations), Communication (84 citations) and Health Informatics (16 citations). Jiang Bian has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Eugene Agichtein, Yandong Liu, Hongyuan Zha, Haoyi Xiong, Ding Zhou, Dejing Dou, Xuhong Li, Ji Liu, Xingjian Li and Xuanyu Wu. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Services Computing, Machine Learning, IEEE Transactions on Multimedia and IEEE Transactions on Emerging Topics in Computational Intelligence.
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.