Xiaoxuan Shen

1.4k total citations · 1 hit paper
38 papers, 915 citations indexed

About

Xiaoxuan Shen is a scholar working on Artificial Intelligence, Information Systems and Computer Science Applications. According to data from OpenAlex, Xiaoxuan Shen has authored 38 papers receiving a total of 915 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 22 papers in Information Systems and 9 papers in Computer Science Applications. Recurrent topics in Xiaoxuan Shen's work include Recommender Systems and Techniques (22 papers), Advanced Graph Neural Networks (15 papers) and Topic Modeling (12 papers). Xiaoxuan Shen is often cited by papers focused on Recommender Systems and Techniques (22 papers), Advanced Graph Neural Networks (15 papers) and Topic Modeling (12 papers). Xiaoxuan Shen collaborates with scholars based in China and United States. Xiaoxuan Shen's co-authors include Zhaoli Zhang, Baolin Yi, Hai Liu, Naixue Xiong, Sannyuya Liu, Jiangbo Shu, Duantengchuan Li, Jiazhang Wang, Ke Lin and Wei Zhang and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Medicine.

In The Last Decade

Xiaoxuan Shen

31 papers receiving 896 citations

Hit Papers

align trajectories

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.

EDMF: Efficient Deep Matrix Factorization With Review Feature Learning for Industrial Recommender System

2021 178 citations Hai Liu, Duantengchuan Li et al. IEEE Transactions on Industrial Informatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaoxuan Shen China	12	495	456	247	127	69	38	915
Hai Liu China	9	372 0.8×	312 0.7×	214 0.9×	63 0.5×	63 0.9×	18	717
Da Cao China	16	491 1.0×	449 1.0×	488 2.0×	85 0.7×	65 0.9×	42	1.0k
Erheng Zhong Hong Kong	18	587 1.2×	372 0.8×	293 1.2×	58 0.5×	89 1.3×	28	1.1k
Deheng Ye China	15	544 1.1×	364 0.8×	85 0.3×	54 0.4×	115 1.7×	29	885
Guang Qiu China	10	1.2k 2.4×	358 0.8×	384 1.6×	50 0.4×	28 0.4×	30	1.7k
Evan Wei Xiang Hong Kong	14	524 1.1×	550 1.2×	192 0.8×	26 0.2×	118 1.7×	20	892
Xin Xin China	19	593 1.2×	625 1.4×	169 0.7×	29 0.2×	135 2.0×	82	1.0k
Xiaomei Yu China	16	600 1.2×	378 0.8×	259 1.0×	42 0.3×	199 2.9×	66	1.1k
Giuseppe Sansonetti Italy	17	288 0.6×	356 0.8×	184 0.7×	31 0.2×	76 1.1×	49	737

Countries citing papers authored by Xiaoxuan Shen

Since Specialization

Citations

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

Fields of papers citing papers by Xiaoxuan Shen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoxuan Shen

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

All Works

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20 of 20 papers shown

1.

Yuan, X., et al.. (2025). Dual-view multi-scale cognitive representation for deep knowledge tracing. Knowledge-Based Systems. 310. 113010–113010. 5 indexed citations

2.

Yi, Baolin, et al.. (2025). Semantic relation-aware graph attention network with noise augmented layer-wise contrastive learning for recommendation. Knowledge-Based Systems. 314. 113217–113217. 3 indexed citations

3.

Shen, Xiaoxuan, et al.. (2025). Enhancing knowledge tracing with question-based contrastive learning. Knowledge-Based Systems. 325. 113899–113899.

4.

Shen, Xiaoxuan, et al.. (2025). Multi-level Contrastive Learning for Knowledge Tracing. ACM Transactions on Knowledge Discovery from Data. 19(8). 1–29.

5.

Shen, Xiaoxuan, et al.. (2025). Recent advances in self-healing polymer-modified asphalt utilizing dynamic covalent bonds. Journal of Polymer Research. 32(1). 7 indexed citations

6.

Yi, Baolin, et al.. (2025). Modeling semantic representation with LLM-enhanced for knowledge-aware recommendation. Information Processing & Management. 63(2). 104387–104387.

7.

Shen, Xiaoxuan, et al.. (2025). Preparation and performance study of commercial polyurethane-modified asphalt. Polymer Bulletin. 83(4).

8.

Yi, Baolin, et al.. (2024). Contrastive multi-interest graph attention network for knowledge-aware recommendation. Expert Systems with Applications. 255. 124748–124748. 5 indexed citations

9.

Shen, Xiaoxuan, et al.. (2024). Revisiting Knowledge Tracing: A Simple and Powerful Model. 263–272. 2 indexed citations

10.

Shen, Xiaoxuan, et al.. (2024). Knowledge-aware fine-grained attention networks with refined knowledge graph embedding for personalized recommendation. Expert Systems with Applications. 249. 123710–123710. 24 indexed citations

11.

Sun, Jianwen, et al.. (2024). Interpretable Knowledge Tracing with Multiscale State Representation. 3265–3276. 11 indexed citations

12.

Liu, Sannyuya, et al.. (2024). Automated discovery of symbolic laws governing skill acquisition from naturally occurring data. Nature Computational Science. 4(5). 334–345. 6 indexed citations

13.

Liu, Sannyuya, et al.. (2023). Hyperbolic embedding of discrete evolution graphs for intelligent tutoring systems. Expert Systems with Applications. 241. 122451–122451. 1 indexed citations

14.

Liu, Sannyuya, et al.. (2023). Heterogeneous Evolution Network Embedding with Temporal Extension for Intelligent Tutoring Systems. ACM Transactions on Information Systems. 42(2). 1–28. 4 indexed citations

15.

Sun, Jianwen, et al.. (2023). Adversarial Bootstrapped Question Representation Learning for Knowledge Tracing. 8016–8025. 9 indexed citations

16.

Sun, Jianwen, et al.. (2023). Weighted Heterogeneous Graph-Based Three-View Contrastive Learning for Knowledge Tracing in Personalized e-Learning Systems. IEEE Transactions on Consumer Electronics. 70(1). 2838–2847. 16 indexed citations

17.

Shen, Xiaoxuan, et al.. (2022). KGAN: Knowledge Grouping Aggregation Network for course recommendation in MOOCs. Expert Systems with Applications. 211. 118344–118344. 27 indexed citations

18.

Shen, Xiaoxuan, et al.. (2022). Autobalanced Multitask Node Embedding Framework for Intelligent Education. IEEE Transactions on Neural Networks and Learning Systems. 35(6). 8653–8667. 2 indexed citations

19.

Liu, Sannyuya, et al.. (2022). Ability boosted knowledge tracing. Information Sciences. 596. 567–587. 22 indexed citations

20.

Liu, Hai, Duantengchuan Li, Xiaoxuan Shen, et al.. (2021). EDMF: Efficient Deep Matrix Factorization With Review Feature Learning for Industrial Recommender System. IEEE Transactions on Industrial Informatics. 18(7). 4361–4371. 178 indexed citations breakdown →

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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