Heng Ji
- Artificial Intelligence top 0.2%
- Information Systems top 1%
- Management Science and Operations Research top 1%
- Computer Vision and Pattern Recognition top 2%
- Molecular Biology
- Topics
- Topic Modeling (117 papers)Natural Language Processing Techniques (87 papers)Advanced Text Analysis Techniques (26 papers)
- Cited by
- Artificial IntelligenceManagement Science and Operations ResearchComputer Science Applications
- Partner nations
- United StatesChinaFrance
In The Last Decade
Heng Ji
152 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 4.0k
- Information Systems 780
- Management Science and Operations Research 572
- Computer Vision and Pattern Recognition 404
- Molecular Biology 340
Countries citing papers authored by Heng Ji
This map shows the geographic impact of Heng Ji'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 Heng Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heng Ji more than expected).
Fields of papers citing papers by Heng Ji
This network shows the impact of papers produced by Heng Ji. 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 Heng Ji. The network helps show where Heng Ji may publish in the future.
Co-authorship network of co-authors of Heng Ji
This figure shows the co-authorship network connecting the top 25 collaborators of Heng Ji. A scholar is included among the top collaborators of Heng Ji 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 Heng Ji. Heng Ji 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 | 1 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 9 | |
| 7 | 6 | |
| 8 | 18 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 5 | |
| 12 | 134 | |
| 13 | 13 | |
| 14 | A Joint Neural Model for Information Extraction with Global Featuresbreakdown → | 225 |
| 15 | 117 | |
| 16 | Learning Phrase Embeddings from Paraphrases with GRUs | 4 |
| 17 | Embracing Non-Traditional Linguistic Resources for Low-resource Language Name Tagging | 6 |
| 18 | Bitext Name Tagging for Cross-lingual Entity Annotation Projection | 7 |
| 19 | Comparison of the Impact of Word Segmentation on Name Tagging for Chinese and Japanese | 40 |
| 20 | Studies for hibernant habitat and hibernant habit of Paederus fuscipes Curtis | 3 |
About Heng Ji
Heng Ji is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 162 papers that have together received 4.6k indexed citations. Recurring topics across this work include Topic Modeling (117 papers), Natural Language Processing Techniques (87 papers) and Advanced Text Analysis Techniques (26 papers). The work is most often cited by research in Artificial Intelligence (4.0k citations), Management Science and Operations Research (572 citations) and Computer Science Applications (199 citations). Heng Ji has collaborated with scholars based in United States, China and France. Frequent co-authors include Qi Li, Ralph Grishman, Jiawei Han, Liang Huang, Lifu Huang, Ying Lin, Clare R. Voss, Lingfei Wu, Fei Huang and Sha Li. Their work appears in journals such as Biomaterials, Knowledge-Based Systems and Nature Human Behaviour.
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.