Ximing Li

1.2k citations
81 papers · 716 indexed · h-index 16
Topics
Topic Modeling (34 papers)Text and Document Classification Technologies (27 papers)Advanced Text Analysis Techniques (16 papers)
Partner nations
ChinaItalyAustralia

In The Last Decade

Ximing Li

73 papers receiving 698 citations

Peers

Ximing Li
Comparison fields: 5 of 81
  • Artificial Intelligence 572
  • Information Systems 149
  • Computer Vision and Pattern Recognition 123
  • General Social Sciences 47
  • Statistical and Nonlinear Physics 45
Replace Jipeng Qiang with:
Jipeng Qiang China
Jiajun Chen China
Xiangyu Song China
Yeyun Gong China
Xianyong Li China
Dinghan Shen United States
Minbyul Jeong South Korea
Aaron Harwood Australia
Saïd Ouatik El Alaoui Morocco
Ximing Li relative to Jipeng Qiang China Jipeng Qiang's profile →
Citations per field
00.5×2.8×
Jipeng Qiang · 1×
Citations per year

Countries citing papers authored by Ximing Li

Since Specialization
Citations

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

Fields of papers citing papers by Ximing Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ximing Li

This figure shows the co-authorship network connecting the top 25 collaborators of Ximing Li. A scholar is included among the top collaborators of Ximing 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 Ximing Li. Ximing 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 6
3 5
4 0
5 3
6 0
7 6
8 1
9 13
10 2
11 22
12 4
13 2
14 8
15 11
16 35
17
A Pseudo Label based Dataless Naive Bayes Algorithm for Text Classification with Seed Words.
12
18 8
19 34
20
Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs
9

About Ximing Li

Ximing Li is a scholar working on Artificial Intelligence, General Social Sciences and Computer Vision and Pattern Recognition, having authored 81 papers that have together received 716 indexed citations. Recurring topics across this work include Topic Modeling (34 papers), Text and Document Classification Technologies (27 papers) and Advanced Text Analysis Techniques (16 papers). The work is most often cited by research in Artificial Intelligence (572 citations), General Social Sciences (47 citations) and Information Systems (149 citations). Ximing Li has collaborated with scholars based in China, Italy and Australia. Frequent co-authors include Jihong Ouyang, Changchun Li, Ang Zhang, Dantong Ouyang, Bo Fu, Jianfeng Qu, Yue Wang, Wen Hua, Yiming Wang and Xiaoyue Feng. Their work appears in journals such as Information Sciences, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.

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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