Youli Qu

26 papers receiving 711 citations

Hit Papers

Feature selection for text classification with Naïve Bayes20082026201420202008100200300400

Peers

Youli Qu
Comparison fields: 5 of 104
  • Artificial Intelligence 596
  • Information Systems 343
  • Computer Vision and Pattern Recognition 134
  • Molecular Biology 51
  • Computational Theory and Mathematics 45
Replace S TAN with:
S TAN China
Jingnian Chen China
Lawrence Shih United States
Lungan Zhang China
Selma Ayşe Özel Türkiye
Eneldo Loza Mencía Germany
Ester Bernadó-Mansilla Spain
Nadim Obeid Jordan
Krishna Kumar Mohbey India
Quinlan United States
Youli Qu relative to S TAN China S TAN's profile →
Citations per field
00.5×1.5×
S TAN · 1×
Citations per year

Countries citing papers authored by Youli Qu

Since Specialization
Citations

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

Fields of papers citing papers by Youli Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Youli Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Youli Qu. A scholar is included among the top collaborators of Youli Qu 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 Youli Qu. Youli Qu 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 1
2 11
3 1
4 1
5 1
6 1
7 1
8
An Algorithm for Calculating Minimal Unsatisfiability-Preserving Subsets of Ontology in DL-Lite
2
9
Summarization using Wikipedia.
6
10 1
11
Algorithm Study of Topic Tracking Based on HowNet and Topic Renewal
0
12 4
13
Method of feature selection for text categorization with bayesian classifiers
4
14 11
15 2
16 5
17 274
18 12
19 1
20
Rerank Method Based on Individual Thesaurus.
13

About Youli Qu

Youli Qu is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications, having authored 27 papers that have together received 784 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (10 papers), Web Data Mining and Analysis (9 papers) and Topic Modeling (8 papers). The work is most often cited by research in Artificial Intelligence (596 citations), Information Systems (343 citations) and Computer Vision and Pattern Recognition (134 citations). Youli Qu has collaborated with scholars based in China, Canada and Netherlands. Frequent co-authors include Houkuan Huang, Shengfeng Tian, Jingnian Chen, Wenqian Shang, Haibin Zhu, Yongmin Lin, Zhihai Wang, Jun Wang, Guowei Xu and Shu Gong. Their work appears in journals such as The Journal of the Acoustical Society of America, Expert Systems with Applications and IEEE Access.

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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