Lungan Zhang

1.1k total citations · 1 hit paper
10 papers, 892 citations indexed

About

Lungan Zhang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Lungan Zhang has authored 10 papers receiving a total of 892 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 4 papers in Information Systems. Recurrent topics in Lungan Zhang's work include Bayesian Modeling and Causal Inference (7 papers), Rough Sets and Fuzzy Logic (6 papers) and Text and Document Classification Technologies (6 papers). Lungan Zhang is often cited by papers focused on Bayesian Modeling and Causal Inference (7 papers), Rough Sets and Fuzzy Logic (6 papers) and Text and Document Classification Technologies (6 papers). Lungan Zhang collaborates with scholars based in China and Australia. Lungan Zhang's co-authors include Liangxiao Jiang, Chaoqun Li, Shasha Wang, Jia Wu, Liangjun Yu and Dianhong Wang and has published in prestigious journals such as Pattern Recognition, Information Sciences and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Lungan Zhang

10 papers receiving 851 citations

Hit Papers

Deep feature weighting fo... 2016 2026 2019 2022 2016 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lungan Zhang China 9 680 234 133 113 52 10 892
Francisco Charte Spain 15 676 1.0× 235 1.0× 176 1.3× 41 0.4× 23 0.4× 41 990
Alexandre Plastino Brazil 18 597 0.9× 343 1.5× 156 1.2× 80 0.7× 84 1.6× 73 1.1k
Shafaatunnur Hasan Malaysia 12 428 0.6× 93 0.4× 100 0.8× 70 0.6× 14 0.3× 38 659
S. R. Balasundaram India 16 535 0.8× 79 0.3× 259 1.9× 35 0.3× 22 0.4× 96 873
Nadim Obeid Jordan 14 400 0.6× 182 0.8× 87 0.7× 41 0.4× 12 0.2× 61 651
Abdulmohsen Algarni Saudi Arabia 14 309 0.5× 169 0.7× 142 1.1× 56 0.5× 41 0.8× 62 717
Can Zhang China 17 336 0.5× 297 1.3× 143 1.1× 49 0.4× 58 1.1× 72 737
Corrado Mencar Italy 18 645 0.9× 106 0.5× 143 1.1× 160 1.4× 12 0.2× 73 981
Quinlan United States 3 412 0.6× 240 1.0× 67 0.5× 146 1.3× 11 0.2× 6 647

Countries citing papers authored by Lungan Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Lungan Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lungan Zhang

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

All Works

10 of 10 papers shown
1.
Jiang, Liangxiao, Lungan Zhang, Chaoqun Li, & Jia Wu. (2018). A Correlation-Based Feature Weighting Filter for Naive Bayes. IEEE Transactions on Knowledge and Data Engineering. 31(2). 201–213. 209 indexed citations
2.
Yu, Liangjun, Liangxiao Jiang, Lungan Zhang, & Dianhong Wang. (2018). Weight Adjusted Naive Bayes. 7. 825–831. 1 indexed citations
3.
Yu, Liangjun, Liangxiao Jiang, Dianhong Wang, & Lungan Zhang. (2018). Toward naive Bayes with attribute value weighting. Neural Computing and Applications. 31(10). 5699–5713. 15 indexed citations
4.
Jiang, Liangxiao, Lungan Zhang, Liangjun Yu, & Dianhong Wang. (2018). Class-specific attribute weighted naive Bayes. Pattern Recognition. 88. 321–330. 153 indexed citations
5.
Zhang, Lungan, Liangxiao Jiang, & Chaoqun Li. (2017). A discriminative model selection approach and its application to text classification. Neural Computing and Applications. 31(4). 1173–1187. 10 indexed citations
6.
Yu, Liangjun, Liangxiao Jiang, Dianhong Wang, & Lungan Zhang. (2017). Attribute Value Weighted Average of One-Dependence Estimators. Entropy. 19(9). 501–501. 23 indexed citations
7.
Jiang, Liangxiao, Chaoqun Li, Shasha Wang, & Lungan Zhang. (2016). Deep feature weighting for naive Bayes and its application to text classification. Engineering Applications of Artificial Intelligence. 52. 26–39. 271 indexed citations breakdown →
8.
Zhang, Lungan, et al.. (2016). Two feature weighting approaches for naive Bayes text classifiers. Knowledge-Based Systems. 100. 137–144. 86 indexed citations
9.
Jiang, Liangxiao, Shasha Wang, Chaoqun Li, & Lungan Zhang. (2015). Structure extended multinomial naive Bayes. Information Sciences. 329. 346–356. 89 indexed citations
10.
Zhang, Lungan, Liangxiao Jiang, & Chaoqun Li. (2015). A New Feature Selection Approach to Naive Bayes Text Classifiers. International Journal of Pattern Recognition and Artificial Intelligence. 30(2). 1650003–1650003. 35 indexed citations

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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