Hang Yang
- Artificial Intelligence top 10%
- Information Systems top 10%
- Signal Processing top 10%
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Co-authors
- Simon FongGuangmin SunRaymond K. WongYvonne HoHuajun ChenSabah MohammedJinan FiaidhiAidong Xu
- Topics
- Data Stream Mining Techniques (25 papers)Anomaly Detection Techniques and Applications (18 papers)Machine Learning and Data Classification (12 papers)
In The Last Decade
Hang Yang
36 papers receiving 220 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 147
- Information Systems 62
- Signal Processing 62
- Computer Networks and Communications 55
- Electrical and Electronic Engineering 24
Countries citing papers authored by Hang Yang
This map shows the geographic impact of Hang Yang'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 Hang Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang Yang more than expected).
Fields of papers citing papers by Hang Yang
This network shows the impact of papers produced by Hang Yang. 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 Hang Yang. The network helps show where Hang Yang may publish in the future.
Co-authorship network of co-authors of Hang Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Hang Yang. A scholar is included among the top collaborators of Hang Yang 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 Hang Yang. Hang Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 6 | |
| 4 | 9 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 6 | |
| 8 | 7 | |
| 9 | 11 | |
| 10 | 17 | |
| 11 | 1 | |
| 12 | 4 | |
| 13 | OVFDT with functional tree leaf — Majority class, naive Bayes and adaptive hybrid integrations | 5 |
| 14 | Optimized very fast decision tree with balanced classification accuracy and compact tree size | 16 |
| 15 | 5 | |
| 16 | An experimental comparison of decision trees in traditional data mining and data stream mining | 4 |
| 17 | Stream mining over fluctuating network traffic at variable data rates | 2 |
| 18 | 10 | |
| 19 | Threaten Quantitative And Analyse Of A Large-scale Network Security Events | 0 |
| 20 | 18 |
About Hang Yang
Hang Yang is a scholar working on Signal Processing, Artificial Intelligence and Management Information Systems, having authored 39 papers that have together received 242 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (25 papers), Anomaly Detection Techniques and Applications (18 papers) and Machine Learning and Data Classification (12 papers). The work is most often cited by research in Signal Processing (62 citations), Artificial Intelligence (147 citations) and Information Systems (62 citations). Hang Yang has collaborated with scholars based in Macao, China and Australia. Frequent co-authors include Simon Fong, Guangmin Sun, Raymond K. Wong, Yvonne Ho, Huajun Chen, Sabah Mohammed, Jinan Fiaidhi, Aidong Xu, Peng Li and Yan Zhuang. Their work appears in journals such as Journal of Systems and Software, Information Systems Frontiers and Mathematical Problems in Engineering.
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.