Jiangzhou Deng

480 total citations
18 papers, 326 citations indexed

About

Jiangzhou Deng is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jiangzhou Deng has authored 18 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Information Systems, 9 papers in Artificial Intelligence and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jiangzhou Deng's work include Recommender Systems and Techniques (17 papers), Sentiment Analysis and Opinion Mining (4 papers) and Expert finding and Q&A systems (3 papers). Jiangzhou Deng is often cited by papers focused on Recommender Systems and Techniques (17 papers), Sentiment Analysis and Opinion Mining (4 papers) and Expert finding and Q&A systems (3 papers). Jiangzhou Deng collaborates with scholars based in China, United States and Australia. Jiangzhou Deng's co-authors include Yong Wang, Junpeng Guo, Jerry Gao, Leo Yu Zhang, Yongheng Deng, Wenhua Li, Xiaoguang Li, Gongying Wang, Songli Wang and Junpeng Guo and has published in prestigious journals such as Expert Systems with Applications, Pattern Recognition and Information Sciences.

In The Last Decade

Jiangzhou Deng

17 papers receiving 318 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jiangzhou Deng China	10	243	122	110	54	46	18	326
Xiaowei Xu China	9	287 1.2×	133 1.1×	121 1.1×	38 0.7×	97 2.1×	39	396
Yan‐Shuo Chang China	6	183 0.8×	130 1.1×	98 0.9×	34 0.6×	43 0.9×	15	283
Surya Kant India	9	146 0.6×	118 1.0×	81 0.7×	38 0.7×	24 0.5×	15	284
Sunita Barve India	7	174 0.7×	128 1.0×	67 0.6×	29 0.5×	60 1.3×	36	313
Yuhan Quan China	5	342 1.4×	344 2.8×	109 1.0×	16 0.3×	53 1.2×	7	498
Wanyu Chen China	13	424 1.7×	407 3.3×	97 0.9×	23 0.4×	51 1.1×	36	562
Yile Liang China	7	299 1.2×	185 1.5×	80 0.7×	18 0.3×	36 0.8×	10	393
Chongming Gao China	9	190 0.8×	185 1.5×	74 0.7×	10 0.2×	23 0.5×	27	327
Jinyang Gao China	9	405 1.7×	324 2.7×	182 1.7×	11 0.2×	68 1.5×	13	567

Countries citing papers authored by Jiangzhou Deng

Since Specialization

Citations

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

Fields of papers citing papers by Jiangzhou Deng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiangzhou Deng

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

All Works

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18 of 18 papers shown

Zhang, Zhiqiang, et al.. (2025). A novel noise reduction and interaction enrichment recommendation model via contrastive learning. Neurocomputing. 645. 130469–130469. 2 indexed citations

Deng, Jiangzhou, et al.. (2025). A simple yet effective enhanced collaborative filtering framework for mitigating noise and data sparsity: evidence from pervasive digital platform datasets. The Journal of Supercomputing. 81(12).

Wang, Yong, et al.. (2024). Matrix factorization recommender based on adaptive Gaussian differential privacy for implicit feedback. Information Processing & Management. 61(4). 103720–103720. 9 indexed citations

Deng, Jiangzhou, et al.. (2024). A linguistically asymmetric similarity decision model integrating item tendency for rating predictions. Journal of Information Science. 1 indexed citations

Deng, Jiangzhou, et al.. (2024). DGRM: Diffusion-GAN recommendation model to alleviate the mode collapse problem in sparse environments. Pattern Recognition. 155. 110692–110692. 12 indexed citations

Deng, Jiangzhou, et al.. (2024). A novel fuzzy neural collaborative filtering for recommender systems. Expert Systems with Applications. 258. 125153–125153. 1 indexed citations

Deng, Jiangzhou, et al.. (2024). A novel joint neural collaborative filtering incorporating rating reliability. Information Sciences. 665. 120406–120406. 9 indexed citations

Deng, Jiangzhou, Hongtao Li, Junpeng Guo, Leo Yu Zhang, & Yong Wang. (2023). Providing prediction reliability through deep neural networks for recommender systems. Computers & Industrial Engineering. 185. 109627–109627. 8 indexed citations

Deng, Jiangzhou, et al.. (2023). Probabilistic Matrix Factorization Recommendation Approach for Integrating Multiple Information Sources. IEEE Transactions on Systems Man and Cybernetics Systems. 53(10). 6220–6231. 11 indexed citations

10.

Li, Wenhua, Xiaoguang Li, Jiangzhou Deng, Yong Wang, & Junpeng Guo. (2021). Sentiment based multi-index integrated scoring method to improve the accuracy of recommender system. Expert Systems with Applications. 179. 115105–115105. 13 indexed citations

11.

Guo, Junpeng, et al.. (2020). An efficient and accurate recommendation strategy using degree classification criteria for item-based collaborative filtering. Expert Systems with Applications. 164. 113756–113756. 27 indexed citations

12.

Deng, Jiangzhou, Junpeng Guo, & Yong Wang. (2019). A Novel K-medoids clustering recommendation algorithm based on probability distribution for collaborative filtering. Knowledge-Based Systems. 175. 96–106. 84 indexed citations

13.

Guo, Junpeng, Jiangzhou Deng, & Yong Wang. (2019). An intuitionistic fuzzy set based hybrid similarity model for recommender system. Expert Systems with Applications. 135. 153–163. 14 indexed citations

14.

Deng, Jiangzhou, Yong Wang, Junpeng Guo, et al.. (2018). A similarity measure based on Kullback–Leibler divergence for collaborative filtering in sparse data. Journal of Information Science. 45(5). 656–675. 12 indexed citations

15.

Wang, Yong, et al.. (2017). A hybrid user similarity model for collaborative filtering. Information Sciences. 418-419. 102–118. 113 indexed citations

16.

Wang, Yong, et al.. (2016). A Collaborative Filtering Recommendation Algorithm Based on Item Probability Distribution. Shuju fenxi yu zhishi faxian. 32(6). 73–79. 2 indexed citations

17.

Cao, Huiying, et al.. (2016). An improved recommendation algorithm based on Bhattacharyya Coefficient. 241–244. 5 indexed citations

18.

Cao, Huiying, et al.. (2016). Competitive recommendation algorithm for E-commerce. 1539–1542. 3 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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