Yong Liu - RankMe

59 papers A* 4A 6B 5C 3Journal 17Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	KANM$^{2}$L: Enhancing Multi-Modal Recommendation With KAN and Dilated Attention. IEEE Trans. Multim. Yi Xue, Qianqian Ren, Yong Liu, Jianguo Sun
2026	A*	`conf`	PHPFND: Detecting Fake News via Post-Hoc Processing of LLMs Hallucination. AAAI Jinke Ma, Jiachen Ma, Wei Zhang, Yong Liu
2025	—	`conf`	A Cross-Modal Fusion Method for Short Video Fake News Detection via MambaFormer. APWeb-WAIM (3) Chunyu Zhang, Liyuan Zhang, Jiachen Ma, Wei Zhang, Yong Liu
2025	J	`jnl`	Adversarial Self-Supervised Learning for Secure and Robust Urban Region Profiling. IEEE Trans. Inf. Forensics Secur. Weiliang Chen, Qianqian Ren, Yong Liu, Jianguo Sun, Feng Lin
2025	—	`conf`	DAFSVFND: Dual Attention Fusion Network for Fake News Detection on Short Video Platforms. ICDAR (3) Ruofan Li, Wei Zhang, Yong Liu
2025	—	`conf`	Graph Contrastive Adversarial Learning for Rumor Detection via Similarity-Preserving. ICIC (16) Jing Dai, Jiachen Ma, Wei Zhang, Yong Liu
2025	B	`conf`	MFSVFND: Multimodal Fusion Network for Detecting Fake News on Short Video Platforms. ICMR Liyuan Zhang, Yang Yajing, Yan Yang, Yong Liu, Zhongyan Gui, Ruofan Li, Hao Fei
2025	—	`conf`	Multimodal GAN Integrating Hypergraph and Knowledge Graph Representations for Synthetic Lethality. ICIC (26) Wei Zhang, Yunlong Wang, Zhijuan Li, Yong Liu, Xiaokun Li, Jiachen Ma
2025	—	`conf`	Resolving Embedding-Ignoring Conflict in Graph Contrastive Learning-Based Rumor Detection. DASFAA (3) Jiachen Ma, Jing Dai, Wei Zhang, Yong Liu
2025	J	`jnl`	Rethinking multi-level information fusion in temporal graphs: Pre-training then distilling for better embedding. Inf. Fusion Meng Liu, Yong Liu, Qianqian Ren, Meng Han
2025	—	`conf`	T 3SVFND: Towards an Evolving Fake News Detector for Emergencies with Test-Time Training on Short Video Platforms. DASFAA (2) Liyuan Zhang, Zeyun Cheng, Zhongyan Gui, Yan Yang, Yong Liu, Jinke Ma
2025	J	`jnl`	When multi-view meets multi-level: A novel spatio-temporal transformer for traffic prediction. Inf. Fusion Jiaqi Lin, Qianqian Ren, Xingfeng Lv, Hui Xu, Yong Liu
2024	—	`conf`	External Knowledge Enhancing Meta-learning Framework for Few-Shot Text Classification via Contrastive Learning and Adversarial Network. APWeb/WAIM (1) Xin Sun, Yan Yang, Yong Liu
2024	A*	`conf`	HeterGCL: Graph Contrastive Learning Framework on Heterophilic Graph. IJCAI Chenhao Wang, Yong Liu, Yan Yang, Wei Li
2024	J	`jnl`	Propagation Structure Fusion for Rumor Detection Based on Node-Level Contrastive Learning. IEEE Trans. Neural Networks Learn. Syst. Jiachen Ma, Yong Liu, Meng Han, Chunqiang Hu, Zhaojie Ju
2023	—	`conf`	A Graph Contrastive Learning Framework with Adaptive Augmentation and Encoding for Unaligned Views. PAKDD (2) Yifu Guo, Yong Liu
2023	—	`conf`	A Transformer-based Multi-modal Joint Attention Fusion Model for Molecular Property Prediction. BIBM Ke Wang, Wei Zhang, Yong Liu
2023	A	`conf`	Contrastive Learning for Rumor Detection via Fitting Beta Mixture Model. CIKM Jiachen Ma, Jing Dai, Yong Liu, Meng Han, Chunyu Ai
2023	A	`conf`	Graph Contrastive Learning with Graph Info-Min. CIKM En Meng, Yong Liu
2023	A	`conf`	Network Embedding with Adaptive Multi-hop Contrast. CIKM Chenhao Wang, Yong Liu, Yan Yang
2023	J	`jnl`	Transformer-enhanced periodic temporal convolution network for long short-term traffic flow forecasting. Expert Syst. Appl. Qianqian Ren, Yang Li, Yong Liu
2022	—	`conf`	A Dynamic Heterogeneous Graph Perception Network with Time-Based Mini-Batch for Information Diffusion Prediction. DASFAA (1) Wei Fan, Meng Liu, Yong Liu
2022	A	`conf`	Curriculum Contrastive Learning for Fake News Detection. CIKM Jiachen Ma, Yong Liu, Meng Liu, Meng Han
2022	—	`conf`	Deep Graph and Sequence Representation Learning for Drug Response Prediction. ICANN (1) Xiangfeng Yan, Yong Liu, Wei Zhang
2022	A	`conf`	Embedding Global and Local Influences for Dynamic Graphs. CIKM Meng Liu, Jiaming Wu, Yong Liu
2022	J	`jnl`	Embedding temporal networks inductively via mining neighborhood and community influences. Appl. Intell. Meng Liu, Ziwei Quan, Jia-Ming Wu, Yong Liu, Meng Han
2022	A	`conf`	Graph Representation Learning via Adaptive Multi-layer Neighborhood Diffusion Contrast. CIKM Jijie Zhang, Yan Yang, Yong Liu, Meng Han, Shaowei Yin
2022	—	`conf`	NE-WNA: A Novel Network Embedding Framework Without Neighborhood Aggregation. ECML/PKDD (2) Jijie Zhang, Yan Yang, Yong Liu, Meng Han
2021	—	`conf`	Dy-Drl2Op: Learning Heuristics for TSP on the Dynamic Graph via Deep Reinforcement Learning. ICONIP (3) Haojie Chen, Jiangting Fan, Yong Liu, Xingfeng Lv
2021	B	`conf`	ETIV: Embedding Temporal Network via Interest Vector. IJCNN Jiangting Fan, Haojie Chen, Jiaming Wu, Yong Liu, Nan Wang
2021	A*	`conf`	Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences. SIGIR Meng Liu, Yong Liu
2021	J	`jnl`	Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences. CoRR Meng Liu, Yong Liu
2021	B	`conf`	MLFF: A Object Detector based on a Multi-Layer Feature Fusion. IJCNN Panyu Peng, Yong Liu, Xingfeng Lv
2021	—	`conf`	SageDy: A Novel Sampling and Aggregating Based Representation Learning Approach for Dynamic Networks. ICANN (5) Jiaming Wu, Meng Liu, Jiangting Fan, Yong Liu, Meng Han
2020	B	`conf`	A New Personalized POI Recommendation Based on Time-Aware and Social Influence. CLOUD Nan Wang, Yong Liu, Peiyao Han, Xiaokun Li, Jinbao Li
2020	—	`conf`	NSTI-IC: An Independent Cascade Model Based on Neighbor Structures and Topic-Aware Interest. APWeb/WAIM (1) Chuhan Zhang, Yueshuang Yin, Yong Liu
2020	C	`conf`	Network Representation Learning Algorithm Based on Neighborhood Influence Sequence. ACML Meng Liu, Ziwei Quan, Yong Liu
2020	B	`conf`	The Collaborative Influence of Multiple Interactions on Successive POI Recommendation. BigData Nan Wang, Yong Liu, Peiyao Han, Xiaokun Li, Jinbao Li
2019	J	`jnl`	Friend and POI recommendation based on social trust cluster in location-based social networks. EURASIP J. Wirel. Commun. Netw. Jinghua Zhu, Chao Wang, Xu Guo, Qian Ming, Jinbao Li, Yong Liu
2019	C	`conf`	Identifying Structural Hole Spanners in Social Networks via Graph Embedding. COCOA Sijie Chen, Ziwei Quan, Yong Liu
2019	C	`conf`	PRME-GTS: A New Successive POI Recommendation Model with Temporal and Social Influences. ADMA Rubai Mao, Zhe Han, Zitu Liu, Yong Liu, Xingfeng Lv, Ping Xuan
2019	—	`conf`	Predicting the Hot Topics with User Sentiments. ICPCSEE (1) Qi Guo, Jinhao Shi, Yong Liu, Xiaokun Li
2019	—	`conf`	Prediction Model for Non-topological Event Propagation in Social Networks. ICPCSEE (1) Zitu Liu, Rui Wang, Yong Liu
2019	—	`conf`	Time Optimal Profit Maximization in a Social Network. APWeb/WAIM (1) Yong Liu, Zitu Liu, Shengnan Xie, Xiaokun Li
2019	—	`conf`	Trust-Aware Group Recommendation with Attention Mechanism in Social Network. MSN Jinghua Zhu, Zhichao Li, Chenbo Yue, Yong Liu
2018	J	`jnl`	A non-negative matrix factorization based method for predicting disease-associated miRNAs in miRNA-disease bilayer network. Bioinform. Yingli Zhong, Ping Xuan, Xiao Wang, Tiangang Zhang, Jianzhong Li, Yong Liu, Weixiong Zhang
2018	—	`conf`	Influence Maximization with Trust Relationship in Social Networks. MSN Nan Wang, Jiansong Da, Jinbao Li, Yong Liu
2018	J	`jnl`	Time Optimal Profit Maximization in a Social Network. Int. J. Web Appl. Yong Liu, Wei Zhang
2018	—	`conf`	Trust-Distrust-Aware Point-of-Interest Recommendation in Location-Based Social Network. WASA Jinghua Zhu, Qian Ming, Yong Liu
2018	—	`conf`	VDTS: A Voronoi Diagram Based Tracking Schemes in Wireless Sensor Networks. CWSN Qianqian Ren, Jinbao Li, Yong Liu
2017	J	`jnl`	A New Structure-Hole-Based Algorithm For Influence Maximization in Large Online Social Networks. IEEE Access Jinghua Zhu, Yong Liu, Xuming Yin
2017	—	`conf`	SA-Min: An Efficient Algorithm for Minimizing the Spread of Influence in a Social Network. CWSN Yong Liu, Zhe Han, Shengshu Shi, Wei Zhang, Ping Xuan
2014	J	`jnl`	A Spatial Correlation Based Adaptive Missing Data Estimation Algorithm in Wireless Sensor Networks. Int. J. Wirel. Inf. Networks Liqiang Pan, Huijun Gao, Hong Gao, Yong Liu
2011	J	`jnl`	Efficient Algorithms for Summarizing Graph Patterns. IEEE Trans. Knowl. Data Eng. Jianzhong Li, Yong Liu, Hong Gao
2011	J	`jnl`	H-cluster: A Novel Efficient Algorithm for Data Clustering in Sensor Networks. J. Commun. Longjiang Guo, Meirui Ren, Jinbao Li, Yong Liu, Chunyu Ai
2010	J	`jnl`	Mining Top-K Graph Patterns that Jointly Maximize Some Significance Measure. J. Comput. Yong Liu, Jianzhong Li, Jinghua Zhu, Hong Gao
2009	—	`conf`	JPMiner: Mining Frequent Jump Patterns from Graph Databases. FSKD (5) Yong Liu, Jianzhong Li, Hong Gao
2008	A*	`conf`	Summarizing Graph Patterns. ICDE Yong Liu, Jianzhong Li, Hong Gao
2007	J	`jnl`	Clustering Frequent Graph Patterns. J. Digit. Inf. Manag. Yong Liu, Jianzhong Li, Jinghua Zhu, Hong Gao