Juanzi Li

14.8k citations
271 papers · 7.5k indexed · 4 hit papers · h-index 42
Topics
Topic Modeling (121 papers)Natural Language Processing Techniques (77 papers)Semantic Web and Ontologies (58 papers)

In The Last Decade

Juanzi Li

246 papers receiving 7.2k citations

Hit Papers

ArnetMiner200820262014202020082023202120224008001.2k

Peers

Juanzi Li
Comparison fields: 5 of 154
  • Artificial Intelligence 5.3k
  • Information Systems 2.2k
  • Statistical and Nonlinear Physics 1.3k
  • Management Science and Operations Research 916
  • Computer Vision and Pattern Recognition 857
Replace Marcos André Gonçalves with:
Marcos André Gonçalves Brazil
Aixin Sun Singapore
Yi Chang United States
James Caverlee United States
Andrew McCallum United States
Prasenjit Mitra United States
Bo Pang United States
Dongwon Lee United States
Lichan Hong United States
Guandong Xu Australia
Juanzi Li relative to Marcos André Gonçalves Brazil Marcos André Gonçalves's profile →
Citations per field
00.5×4.3×
Marcos André Gonçalves · 1×
Citations per year

Countries citing papers authored by Juanzi Li

Since Specialization
Citations

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

Fields of papers citing papers by Juanzi Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juanzi Li

This figure shows the co-authorship network connecting the top 25 collaborators of Juanzi Li. A scholar is included among the top collaborators of Juanzi 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 Juanzi Li. Juanzi Li 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
#WorkIndexed citations
1 0
2 0
3 1
4 1
5 6
6 1
7 3
8 0
9 3
10 21
11 4
12 2
13 7
14 8
15 0
16 5
17 71
18 74
19 2
20 0

About Juanzi Li

Juanzi Li is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 271 papers that have together received 7.5k indexed citations. Recurring topics across this work include Topic Modeling (121 papers), Natural Language Processing Techniques (77 papers) and Semantic Web and Ontologies (58 papers). The work is most often cited by research in Artificial Intelligence (5.3k citations), Statistical and Nonlinear Physics (1.3k citations) and Information Systems (2.2k citations). Juanzi Li has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Jie Tang, Zhong Su, Limin Yao, Jing Zhang, Li Zhang, Zhiyuan Liu, Lei Hou, Xiaozhi Wang, Maosong Sun and Zhichun Wang. Their work appears in journals such as Chemical Engineering Journal, Polymer and Expert Systems with Applications.

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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