Hua-Fu Li
- Information Systems top 1%
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Computational Theory and Mathematics top 2%
- Computer Networks and Communications top 10%
- Co-authors
- Suh-Yin LeeMan-Kwan ShanFang-Fei KuoYi‐Cheng ChenJiun‐Long HuangXiaokun WangYawei ZhangChunming Wang
- Topics
- Data Mining Algorithms and Applications (28 papers)Data Stream Mining Techniques (15 papers)Data Management and Algorithms (15 papers)
- Partner nations
- TaiwanChinaUnited Kingdom
In The Last Decade
Hua-Fu Li
37 papers receiving 586 citations
Peers
Comparison fields: 5 of 53
- Information Systems 511
- Artificial Intelligence 336
- Signal Processing 287
- Computational Theory and Mathematics 283
- Computer Networks and Communications 141
Countries citing papers authored by Hua-Fu Li
This map shows the geographic impact of Hua-Fu Li'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 Hua-Fu Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hua-Fu Li more than expected).
Fields of papers citing papers by Hua-Fu Li
This network shows the impact of papers produced by Hua-Fu Li. 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 Hua-Fu Li. The network helps show where Hua-Fu Li may publish in the future.
Co-authorship network of co-authors of Hua-Fu Li
This figure shows the co-authorship network connecting the top 25 collaborators of Hua-Fu Li. A scholar is included among the top collaborators of Hua-Fu Li 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 Hua-Fu Li. Hua-Fu Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | A SINGLE-SCAN ALGORITHM FOR MINING SEQUENTIAL PATTERNS FROM DATA STREAMS | 3 |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 32 | |
| 6 | ANN-based Reliability Redundancy Optimization for Complex System | 1 |
| 7 | 9 | |
| 8 | 11 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 54 | |
| 12 | 116 | |
| 13 | 15 | |
| 14 | 14 | |
| 15 | 41 | |
| 16 | 9 | |
| 17 | 12 | |
| 18 | 2 | |
| 19 | An Efficient Algorithm for Mining Frequent Itemests over the Entire History of Data Streams | 67 |
| 20 | 3 |
About Hua-Fu Li
Hua-Fu Li is a scholar working on Signal Processing, Information Systems and Computational Theory and Mathematics, having authored 38 papers that have together received 638 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (28 papers), Data Stream Mining Techniques (15 papers) and Data Management and Algorithms (15 papers). The work is most often cited by research in Signal Processing (287 citations), Information Systems (511 citations) and Computational Theory and Mathematics (283 citations). Hua-Fu Li has collaborated with scholars based in Taiwan, China and United Kingdom. Frequent co-authors include Suh-Yin Lee, Man-Kwan Shan, Fang-Fei Kuo, Yi‐Cheng Chen, Jiun‐Long Huang, Xiaokun Wang, Yawei Zhang, Chunming Wang, Guangyin Zhao and Xing Xiao. Their work appears in journals such as Expert Systems with Applications, Pattern Recognition Letters and Computer Networks.
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.