Ou Jin
- Artificial Intelligence top 2%
- Information Systems top 1%
- Computer Vision and Pattern Recognition top 5%
- Statistical and Nonlinear Physics top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Yong YuQiang YangJunfeng PanA. AtallahXinran HeTao XuTian-Bing XuBo Liu
- Topics
- Topic Modeling (3 papers)Advanced Text Analysis Techniques (3 papers)Text and Document Classification Technologies (3 papers)
- Journals
- Diagnostic PathologyInternational Journal of Digital Content Technology and its ApplicationsRare & Special e-Zone (The Hong Kong University of Science and Technology)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Ou Jin
15 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Artificial Intelligence 611
- Information Systems 467
- Computer Vision and Pattern Recognition 225
- Statistical and Nonlinear Physics 130
- Computer Networks and Communications 111
Countries citing papers authored by Ou Jin
This map shows the geographic impact of Ou Jin'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 Ou Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ou Jin more than expected).
Fields of papers citing papers by Ou Jin
This network shows the impact of papers produced by Ou Jin. 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 Ou Jin. The network helps show where Ou Jin may publish in the future.
Co-authorship network of co-authors of Ou Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Ou Jin. A scholar is included among the top collaborators of Ou Jin 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 Ou Jin. Ou Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 7 | |
| 3 | Practical Lessons from Predicting Clicks on Ads at Facebookbreakdown → | 515 |
| 4 | 10 | |
| 5 | Cross-Domain Co-Extraction of Sentiment and Topic Lexicons | 86 |
| 6 | 189 | |
| 7 | 154 | |
| 8 | 3 | |
| 9 | Data Preprocessing Method for Web Usage Mining | 2 |
| 10 | Desiging and Implementation of GPRS Network Vending Machine Based on IC Card Payed | 0 |
| 11 | 12 | |
| 12 | 8 | |
| 13 | 65 | |
| 14 | 7 | |
| 15 | Research on Enterprise Track of TREC 2007 at SJTU APEX Lab | 10 |
| 16 | The existing state of enhanced oil recovery by utilizing carbon dioxide | 3 |
About Ou Jin
Ou Jin is a scholar working on Artificial Intelligence, Health Information Management and Information Systems, having authored 16 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Advanced Text Analysis Techniques (3 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Information Systems (467 citations), Artificial Intelligence (611 citations) and Computational Mathematics (8 citations). Ou Jin has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yong Yu, Qiang Yang, Junfeng Pan, A. Atallah, Xinran He, Tao Xu, Tian-Bing Xu, Bo Liu, Ralf Herbrich and Joaquin Quiñonero Candela. Their work appears in journals such as Diagnostic Pathology, International Journal of Digital Content Technology and its Applications and Rare & Special e-Zone (The Hong Kong University of Science 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.