Chong Feng

1.3k total citations
79 papers, 797 citations indexed

About

Chong Feng is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Chong Feng has authored 79 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 16 papers in Information Systems and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Chong Feng's work include Topic Modeling (44 papers), Natural Language Processing Techniques (32 papers) and Advanced Text Analysis Techniques (19 papers). Chong Feng is often cited by papers focused on Topic Modeling (44 papers), Natural Language Processing Techniques (32 papers) and Advanced Text Analysis Techniques (19 papers). Chong Feng collaborates with scholars based in China, Pakistan and Nigeria. Chong Feng's co-authors include Heyan Huang, Arshad Ahmad, Ge Shi, Yashen Wang, Abdallah Yousif, Xian-Ling Mao, Kan Li, Ming Lei, Xiaochi Wei and Xiangnan He and has published in prestigious journals such as IEEE Access, Frontiers in Immunology and ACM Computing Surveys.

In The Last Decade

Chong Feng

70 papers receiving 765 citations

Peers

Chong Feng
Comparison fields: 5 of 103
  • Artificial Intelligence 469
  • Information Systems 258
  • Computer Vision and Pattern Recognition 117
  • Computer Networks and Communications 69
  • Management Science and Operations Research 58
Replace Từ Minh Phương with:
Từ Minh Phương Vietnam
László Kovács Hungary
Deheng Ye China
Lawrence Shih United States
Mark Truran United Kingdom
Ce Zhang China
Mimmo Parente Italy
Vikram Pudi India
Jack Wu Hong Kong
Từ Minh Phương Vietnam View profile →
Citations per field, relative to Chong Feng
Chong Feng · 1×
Citations per year, relative to Chong Feng
Chong Feng · 1×

Countries citing papers authored by Chong Feng

Since Specialization
Citations

This map shows the geographic impact of Chong Feng'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 Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chong Feng more than expected).

Fields of papers citing papers by Chong Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chong Feng. 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 Feng. The network helps show where Chong Feng may publish in the future.

Co-authorship network of co-authors of Chong Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Chong Feng. A scholar is included among the top collaborators of Chong Feng 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 Chong Feng. Chong Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 5
3 0
4 2
5 1
6 5
7 2
8 25
9 1
10 35
11 0
12
Co-Extracting Opinion Targets and Opinion-Bearing Words in Chinese Micro-Blog Texts
2
13
Emotional Tendency Identification for Micro-blog Topics Based on Multiple Characteristics
9
14
Substring reduction algorithm based on independence statistic
1
15
0.98μm変換効率ダイオードレーザのための非対称広い導波路構造【Powered by NICT】
1
16
Recognition of Complex Maximal Length Noun Phrase Using Conditional Random Fields
2
17
Active Learning in Chinese Word Segmentation Based on Multigram Language Model
0
18
Organization Names Recognition with Active Learning
1
19
Inter-rater agreement on the classification of job titles
3
20
Knowledge Extraction from Text: Machine Learning for Text-to-rule Translation
2

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.

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