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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Time-aware Path Reasoning on Knowledge Graph for Recommendation
Yuyue Zhao, Xiang Wang, Jiawei Chen, et al.
ACM transactions on office information systems (2022) Vol. 41, Iss. 2, pp. 1-26
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multi-Modal
Ke Liang, Lingyuan Meng, Meng Liu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 12, pp. 9456-9478
Open Access | Times Cited: 47
Attention Is Not the Only Choice: Counterfactual Reasoning for Path-Based Explainable Recommendation
Yicong Li, Xiangguo Sun, Hongxu Chen, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 9, pp. 4458-4471
Open Access | Times Cited: 13
Multi-View Enhanced Graph Attention Network for Session-Based Music Recommendation
Dongjing Wang, Xin Zhang, Yuyu Yin, et al.
ACM transactions on office information systems (2023) Vol. 42, Iss. 1, pp. 1-30
Open Access | Times Cited: 19
A Survey on Knowledge Graph-Based Recommender Systems
Dongze Li, Hanbing Qu, Jiaqiang Wang
2021 China Automation Congress (CAC) (2023), pp. 2925-2930
Closed Access | Times Cited: 12
Broad information diffusion modeling for sharing link click prediction using knowledge graphs
Xiangjie Kong, Can Shu, Lingyun Wang, et al.
Expert Systems with Applications (2025), pp. 127276-127276
Closed Access
User Perception of Recommendation Explanation: Are Your Explanations What Users Need?
Hongyu Lu, Weizhi Ma, Yifan Wang, et al.
ACM transactions on office information systems (2022) Vol. 41, Iss. 2, pp. 1-31
Closed Access | Times Cited: 19
Enriching interactive explanations with fuzzy temporal constraint networks
Mariña Canabal-Juanatey, José M. Alonso, Alejandro Català, et al.
International Journal of Approximate Reasoning (2024) Vol. 171, pp. 109128-109128
Open Access | Times Cited: 3
Explainable Deep Reinforcement Learning for Knowledge Graph Reasoning
Di Wang
Advances in computational intelligence and robotics book series (2023), pp. 168-183
Closed Access | Times Cited: 7
DHyper: A Recurrent Dual Hypergraph Neural Network for Event Prediction in Temporal Knowledge Graphs
Xing Tang, Ling Chen, Shi Hong-Yu, et al.
ACM transactions on office information systems (2024) Vol. 42, Iss. 5, pp. 1-23
Closed Access | Times Cited: 2
TGLite: A Lightweight Programming Framework for Continuous-Time Temporal Graph Neural Networks
Yufeng Wang, Charith Mendis
(2024), pp. 1183-1199
Closed Access | Times Cited: 2
Contrastive multi-interest graph attention network for knowledge-aware recommendation
Jianfang Liu, Wei Wang, Baolin Yi, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124748-124748
Closed Access | Times Cited: 2
A review of graph neural networks and pretrained language models for knowledge graph reasoning
Jiangtao Ma, Бо Лю, Kunlin Li, et al.
Neurocomputing (2024) Vol. 609, pp. 128490-128490
Closed Access | Times Cited: 2
Explainable Session-based Recommendation via Path Reasoning
Yang Cao, Shuo Shang, Jun Wang, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 37, Iss. 1, pp. 278-290
Closed Access | Times Cited: 2
Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning
Ruijie Wang, Zheng Li, Jingfeng Yang, et al.
Proceedings of the ACM Web Conference 2022 (2023), pp. 2621-2632
Open Access | Times Cited: 6
Dynamic Recommendation Based on Graph Diffusion and Ebbinghaus Curve
Zhihong Cui, Xiangguo Sun, Hongxu Chen, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 2, pp. 2755-2764
Closed Access | Times Cited: 6
Modeling users’ preference changes in recommender systems via time-dependent Markov random fields
Abinash Pujahari, Dilip Singh Sisodia
Expert Systems with Applications (2023) Vol. 234, pp. 121072-121072
Closed Access | Times Cited: 6
Search to Pass Messages for Temporal Knowledge Graph Completion
Zhen Wang, Haotong Du, Quanming Yao, et al.
(2022), pp. 6160-6172
Open Access | Times Cited: 10
Knowledge Graph-Based Behavior Denoising and Preference Learning for Sequential Recommendation
Hongzhi Liu, Yao Zhu, Zhonghai Wu
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 6, pp. 2490-2503
Closed Access | Times Cited: 5
Recommendations with residual connections and negative sampling based on knowledge graphs
Yuanyuan Liu, Zhaoqian Zhong, Chao Che, et al.
Knowledge-Based Systems (2022) Vol. 258, pp. 110049-110049
Closed Access | Times Cited: 8
Impact of temporal context on recommender systems along global timeline
Yitong Ji
(2024)
Open Access | Times Cited: 1
Explainable Recommender Systems with Knowledge Graphs and Language Models
Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, et al.
Lecture notes in computer science (2024), pp. 352-357
Closed Access | Times Cited: 1
Towards Knowledge-Aware and Deep Reinforced Cross-Domain Recommendation Over Collaborative Knowledge Graph
Yakun Li, Lei Hou, Juanzi Li
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 11, pp. 7171-7187
Closed Access | Times Cited: 1
Adaptive Graph Neural Network with Incremental Learning Mechanism for Knowledge Graph Reasoning
Junhui Zhang, Hongying Zan, Shuning Wu, et al.
Electronics (2024) Vol. 13, Iss. 14, pp. 2778-2778
Open Access | Times Cited: 1
Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation
Jihu Wang, Yuliang Shi, Han Yu, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023), pp. 372-382
Closed Access | Times Cited: 3
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