Guangyou Zhou

3.6k total citations · 1 hit paper
70 papers, 2.3k citations indexed

About

Guangyou Zhou is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Guangyou Zhou has authored 70 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Artificial Intelligence, 21 papers in Information Systems and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Guangyou Zhou's work include Topic Modeling (56 papers), Advanced Graph Neural Networks (22 papers) and Natural Language Processing Techniques (18 papers). Guangyou Zhou is often cited by papers focused on Topic Modeling (56 papers), Advanced Graph Neural Networks (22 papers) and Natural Language Processing Techniques (18 papers). Guangyou Zhou collaborates with scholars based in China, Canada and United States. Guangyou Zhou's co-authors include Kang Liu, Jun Zhao, Siwei Lai, Daojian Zeng, Jun Zhao, Jimmy Xiangji Huang, Zhiwen Xie, Tingting He, Cai Li and Wensheng Wu and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Pattern Recognition.

In The Last Decade

Guangyou Zhou

67 papers receiving 2.3k citations

Hit Papers

Relation Classification via Convolutional Deep Neural Net... 2014 2026 2018 2022 2014 250 500 750
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. Relation Classification via Convolutional Deep Neural Network
    2014 862 citations Daojian Zeng, Kang Liu et al. profile →

Peers

Guangyou Zhou
Massimiliano Ciaramita United States
Zuhair Bandar United Kingdom
Huan Sun United States
Dimitris Kontokostas Germany
Georgi Kobilarov Germany
Michele Banko United States
Mohamed Morsey Germany
Yunbo Cao China
Max Jakob Germany
Massimiliano Ciaramita United States
Guangyou Zhou
Citations per year, relative to Guangyou Zhou Guangyou Zhou (= 1×) peers Massimiliano Ciaramita

Countries citing papers authored by Guangyou Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Guangyou Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guangyou Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Guangyou Zhou. A scholar is included among the top collaborators of Guangyou Zhou 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 Guangyou Zhou. Guangyou Zhou 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.
Xie, Zhiwen, et al.. (2025). LE-DLCM: Decoupled learner and course modeling with large language models for enhanced course recommendation. Knowledge-Based Systems. 334. 115135–115135.
2.
3.
Zhou, Guangyou, et al.. (2025). A diversity-enhanced knowledge distillation model for practical math word problem solving. Information Processing & Management. 62(3). 104059–104059. 7 indexed citations
4.
Yu, Guanying, et al.. (2025). Exploring long- and short-term knowledge state graph representations with adaptive fusion for knowledge tracing. Information Processing & Management. 62(3). 104074–104074. 5 indexed citations
5.
Tao, Xingyu, et al.. (2025). Unifying the syntax and semantics for math word problem solving. Neurocomputing. 636. 130042–130042. 1 indexed citations
6.
7.
Xie, Zhiwen, et al.. (2024). One Subgraph for All: Efficient Reasoning on Opening Subgraphs for Inductive Knowledge Graph Completion. IEEE Transactions on Knowledge and Data Engineering. 36(12). 8914–8927. 11 indexed citations
8.
Liu, Jin, et al.. (2024). Question-Directed Reasoning With Relation-Aware Graph Attention Network for Complex Question Answering Over Knowledge Graph. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 1915–1927. 6 indexed citations
9.
Xie, Zhiwen, et al.. (2023). Learning Query Adaptive Anchor Representation for Inductive Relation Prediction. 14041–14053. 2 indexed citations
10.
Zhang, Yi, Guangyou Zhou, Zhiwen Xie, & Jimmy Xiangji Huang. (2023). Number-enhanced representation with hierarchical recursive tree decoding for math word problem solving. Information Processing & Management. 61(2). 103585–103585. 5 indexed citations
11.
Zhou, Guangyou, et al.. (2023). Incorporating global–local neighbors with Gaussian mixture embedding for few-shot knowledge graph completion. Expert Systems with Applications. 234. 121086–121086. 7 indexed citations
12.
Liu, Jin, et al.. (2022). Query Path Generation via Bidirectional Reasoning for Multihop Question Answering From Knowledge Bases. IEEE Transactions on Cognitive and Developmental Systems. 15(3). 1183–1195. 8 indexed citations
13.
Wei, Wei, et al.. (2020). Position-aware self-attention based neural sequence labeling. Pattern Recognition. 110. 107636–107636. 23 indexed citations
14.
Xie, Zhiwen, Guangyou Zhou, Jin Liu, & Jimmy Xiangji Huang. (2020). ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding. 5929–5939. 41 indexed citations
15.
Liu, Jin, et al.. (2017). Scalable tag recommendation for software information sites. 272–282. 38 indexed citations
16.
Zhou, Guangyou, Tingting He, Jun Zhao, & Wensheng Wu. (2015). A subspace learning framework for cross-lingual sentiment classification with partial parallel data. International Conference on Artificial Intelligence. 1426–1432. 14 indexed citations
17.
Zhou, Guangyou, Tingting He, Wensheng Wu, & Xiaohua Hu. (2015). Linking heterogeneous input features with pivots for domain adaptation. International Conference on Artificial Intelligence. 1419–1425. 14 indexed citations
18.
Zhou, Guangyou, Yubo Chen, Daojian Zeng, & Jun Zhao. (2014). Group Non-negative Matrix Factorization with Natural Categories for Question Retrieval in Community Question Answer Archives. International Conference on Computational Linguistics. 89–98. 6 indexed citations
19.
He, Shizhu, Shulin Liu, Yubo Chen, et al.. (2013). CASIA@QALD-3: A Question Answering System over Linked Data. CLEF (Working Notes). 15 indexed citations
20.
Zhou, Guangyou, et al.. (2011). Exploiting Web-Derived Selectional Preference to Improve Statistical Dependency Parsing. Meeting of the Association for Computational Linguistics. 1556–1565. 28 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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