Liangxiao Jiang

5.1k total citations · 1 hit paper
114 papers, 3.6k citations indexed

About

Liangxiao Jiang is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Liangxiao Jiang has authored 114 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Artificial Intelligence, 38 papers in Information Systems and 28 papers in Computational Theory and Mathematics. Recurrent topics in Liangxiao Jiang's work include Bayesian Modeling and Causal Inference (41 papers), Machine Learning and Data Classification (41 papers) and Imbalanced Data Classification Techniques (40 papers). Liangxiao Jiang is often cited by papers focused on Bayesian Modeling and Causal Inference (41 papers), Machine Learning and Data Classification (41 papers) and Imbalanced Data Classification Techniques (40 papers). Liangxiao Jiang collaborates with scholars based in China, Canada and Australia. Liangxiao Jiang's co-authors include Chaoqun Li, Zhihua Cai, Lungan Zhang, Dianhong Wang, Huan Zhang, Liangjun Yu, H. Zhang, Shasha Wang, Harry Zhang and Jia Wu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and Expert Systems with Applications.

In The Last Decade

Liangxiao Jiang

108 papers receiving 3.4k citations

Hit Papers

Deep feature weighting for naive Bayes and its applicatio... 2016 2026 2019 2022 2016 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep feature weighting for naive Bayes and its application to text classification
    2016 271 citations Liangxiao Jiang, Chaoqun Li et al. Engineering Applications of Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liangxiao Jiang China 31 2.6k 772 548 456 383 114 3.6k
Alberto Cano United States 30 1.7k 0.7× 448 0.6× 357 0.7× 173 0.4× 362 0.9× 93 2.6k
María José del Jesús Spain 34 4.5k 1.7× 1.3k 1.7× 611 1.1× 866 1.9× 195 0.5× 108 5.7k
Chaoqun Li China 25 1.4k 0.6× 395 0.5× 352 0.6× 198 0.4× 316 0.8× 72 2.0k
Kalyan Veeramachaneni United States 21 1.3k 0.5× 363 0.5× 365 0.7× 329 0.7× 135 0.4× 82 2.5k
Petra Perner Germany 19 2.0k 0.8× 1.6k 2.1× 670 1.2× 620 1.4× 106 0.3× 105 4.2k
Bernardete Ribeiro Portugal 28 1.2k 0.5× 228 0.3× 476 0.9× 246 0.5× 161 0.4× 210 3.0k
Carlos Soares Portugal 24 1.6k 0.6× 368 0.5× 260 0.5× 254 0.6× 69 0.2× 126 2.9k
Isaac Triguero Spain 30 2.2k 0.9× 525 0.7× 772 1.4× 310 0.7× 55 0.1× 90 3.5k
Ioannis Vlahavas Greece 30 3.4k 1.3× 1.3k 1.7× 1.1k 2.1× 170 0.4× 117 0.3× 179 5.1k
Yong Liu China 37 1.7k 0.7× 1.9k 2.5× 744 1.4× 499 1.1× 148 0.4× 225 4.6k

Countries citing papers authored by Liangxiao Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Liangxiao Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liangxiao Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Liangxiao Jiang. A scholar is included among the top collaborators of Liangxiao Jiang 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 Liangxiao Jiang. Liangxiao Jiang 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
1.
Zhang, Zhun, Liangxiao Jiang, Zhichao Liu, et al.. (2025). WirMAE: Learning Well-Logging Interval Representations via Masked Autoencoders for Gas Hydrate Reservoir Characterization. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–16.
2.
Zhang, Huan, et al.. (2025). Dual-View Learning from Crowds. ACM Transactions on Knowledge Discovery from Data. 19(3). 1–21. 2 indexed citations
3.
Jiang, Liangxiao, et al.. (2024). Instance redistribution-based label integration for crowdsourcing. Information Sciences. 674. 120702–120702. 4 indexed citations
4.
Liu, Yuanyuan, Tengfei Liu, Haoyu Zhang, et al.. (2024). Token-disentangling Mutual Transformer for multimodal emotion recognition. Engineering Applications of Artificial Intelligence. 133. 108348–108348. 11 indexed citations
5.
Jiang, Liangxiao, et al.. (2024). Three-way decision-based label integration for crowdsourcing. Pattern Recognition. 158. 111034–111034. 2 indexed citations
6.
Jiang, Liangxiao, et al.. (2024). Worker Similarity-Based Label Completion for Crowdsourcing. IEEE Transactions on Big Data. 11(2). 710–721.
7.
Jiang, Liangxiao, et al.. (2024). Label Consistency-Based Ground Truth Inference for Crowdsourcing. IEEE Transactions on Neural Networks and Learning Systems. 36(5). 9408–9421. 2 indexed citations
8.
Jiang, Liangxiao, et al.. (2024). DDRANet: A Dynamic Density-Region-Aware Network for Crowd Counting. IEEE Signal Processing Letters. 31. 2165–2169. 1 indexed citations
9.
Jiang, Liangxiao, et al.. (2023). Three-way decision-based noise correction for crowdsourcing. International Journal of Approximate Reasoning. 160. 108973–108973. 6 indexed citations
10.
Jiang, Liangxiao, et al.. (2022). Attribute augmentation-based label integration for crowdsourcing. Frontiers of Computer Science. 17(5). 21 indexed citations
11.
Zhang, Huan & Liangxiao Jiang. (2022). Fine tuning attribute weighted naive Bayes. Neurocomputing. 488. 402–411. 14 indexed citations
12.
Yu, Dong, Liangxiao Jiang, & Chaoqun Li. (2021). Improving data and model quality in crowdsourcing using co-training-based noise correction. Information Sciences. 583. 174–188. 46 indexed citations
13.
Xu, Wenqiang, Liangxiao Jiang, & Chaoqun Li. (2020). Resampling-based noise correction for crowdsourcing. Journal of Experimental & Theoretical Artificial Intelligence. 33(6). 985–999. 7 indexed citations
14.
Zhang, Hao, Liangxiao Jiang, & Wenqiang Xu. (2019). Multiple Noisy Label Distribution Propagation for Crowdsourcing. 1473–1479. 15 indexed citations
15.
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
16.
Jiang, Liangxiao & Chaoqun Li. (2018). Two improved attribute weighting schemes for value difference metric. Knowledge and Information Systems. 60(2). 949–970. 7 indexed citations
17.
Wang, Dianhong & Liangxiao Jiang. (2007). An Improved Attribute Selection Measure for Decision Tree Induction. 654–658. 21 indexed citations
18.
Yang, Xiaoyong, et al.. (2006). Geochemical Study of Shaxi Porphyry Copper-Gold Deposit in Southern Part of Tan-Lu Fault Belt, East China. Journal of the Geological Society of India. 67(4). 475–494.
19.
Zhang, Harry, Liangxiao Jiang, & Su Jiang. (2005). Hidden naive Bayes. National Conference on Artificial Intelligence. 919–924. 59 indexed citations
20.
Jiang, Liangxiao & H. Zhang. (2005). Learning instance greedily cloning naive Bayes for ranking. 8 pp.–8 pp.. 12 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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