Chong Teng
- Artificial Intelligence top 5%
- Topic Modeling 24
- Natural Language Processing Techniques 15
- Advanced Text Analysis Techniques 13
- Sentiment Analysis and Opinion Mining 9
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- Web Data Mining and Analysis 2
- General Social Sciences top 10%
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- Biomedical Text Mining and Ontologies 3
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- Complex Network Analysis Techniques 3
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- Misinformation and Its Impacts 2
- Co-authors
- Donghong JiHao FeiFei LiJingye LiShengqiong WuJiang LiuMeishan ZhangBobo Li
In The Last Decade
Chong Teng
29 papers receiving 323 citations
Hit Papers
Peers
Comparison fields: 5 of 51
- Artificial Intelligence 294
- Management Science and Operations Research 48
- Information Systems 44
- General Social Sciences 6
- Computer Vision and Pattern Recognition 30
Countries citing papers authored by Chong Teng
This map shows the geographic impact of Chong Teng'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 Chong Teng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chong Teng more than expected).
Fields of papers citing papers by Chong Teng
This network shows the impact of papers produced by Chong Teng. 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 Chong Teng. The network helps show where Chong Teng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chong Teng, 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 | 2 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 8 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 3 | |
| 10 | 2024 | 0 | |
| 11 | 2023 | 5 | |
| 12 | 2023 | 3 | |
| 13 | 2023 | 1 | |
| 14 | 2022 | 17 | |
| 15 | Word Sense Induction Using Lexical Chain based Hypergraph Model | 2014 | 4 |
| 16 | Context-Enhanced Personalized Social Summarization | 2012 | 9 |
| 17 | Social Summarization via Automatically Discovered Social Context | 2011 | 7 |
| 18 | Query-Focused Multi-Document Summarization Using Co-Training Based Semi-Supervised Learning | 2009 | 1 |
| 19 | 2009 | 2 | |
| 20 | Multi-Strategy Question Answering System for NTCIR-7 C-C Task. | 2008 | 3 |
About Chong Teng
Chong Teng is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 335 indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Natural Language Processing Techniques (15 papers), Advanced Text Analysis Techniques (13 papers), Sentiment Analysis and Opinion Mining (9 papers), Biomedical Text Mining and Ontologies (3 papers), Complex Network Analysis Techniques (3 papers), Misinformation and Its Impacts (2 papers) and Web Data Mining and Analysis (2 papers). The work is most often cited by research in Artificial Intelligence (294 citations), Management Science and Operations Research (48 citations) and Information Systems (44 citations). Chong Teng has collaborated with scholars based in China, Singapore and Australia. Frequent co-authors include Donghong Ji, Hao Fei, Fei Li, Jingye Li, Shengqiong Wu, Jiang Liu, Meishan Zhang, Bobo Li, Yanxiang He and Donghong Ji. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Information Sciences, Mathematical and Computer Modelling, Knowledge-Based Systems and Engineering Applications of Artificial 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.