16 citations · 36 across the 7 of their papers we have counts for
7 papers
Learnable Model Augmentation Self-Supervised Learning for Sequential Recommendation
Yongjing Hao, Pengpeng Zhao, Xuefeng Xian +5
Sequential Recommendation aims to predict the next item based on user behaviour. Recently, Self-Supervised Learning (SSL) has been proposed to improve recommendation performance. H…
A Unified Framework for Cross-Domain and Cross-System Recommendations
Feng Zhu, Yan Wang, Jun Zhou +3
Cross-Domain Recommendation (CDR) and Cross-System Recommendation (CSR) have been proposed to improve the recommendation accuracy in a target dataset (domain/system) with the help…
Social Group Query Based on Multi-fuzzy-constrained Strong Simulation
Guliu Liu, Lei Li, Guanfeng Liu +1
Traditional social group analysis mostly uses interaction models, event models, or other methods to identify and distinguish groups. This type of method can divide social participa…
Cross-Domain Recommendation: Challenges, Progress, and Prospects
Feng Zhu, Yan Wang, Chaochao Chen +3
To address the long-standing data sparsity problem in recommender systems (RSs), cross-domain recommendation (CDR) has been proposed to leverage the relatively richer information f…
Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications
Chaochao Chen, Jamie Cui, Guanfeng Liu +2
Knowledge Graph (KG) has attracted more and more companies' attention for its ability to connect different types of data in meaningful ways and support rich data services. However,…
A Deep Framework for Cross-Domain and Cross-System Recommendations
Feng Zhu, Yan Wang, Chaochao Chen +3
Cross-Domain Recommendation (CDR) and Cross-System Recommendations (CSR) are two of the promising solutions to address the long-standing data sparsity problem in recommender system…