Results 1 to 10 of about 226 (67)
Cross-domain recommendation in MOOCs: A graph capsule network approach with transfer learning
Computers and Education: Artificial IntelligenceCross-domain recommendation systems enhance target domain performance through multi-domain knowledge integration. With the rapid development of artificial intelligence, the growing demand for programming skills has intensified the need for joint ...
Lian Yuanfeng, Zhuang Yongqi
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Cross-domain Recommendation Algorithm Based on Self-attention Mechanism and Transfer Learning [PDF]
Jisuanji kexue, 2022 Traditional single-domain recommendation algorithm is limited by the sparse relationship between users and items,and there is a problem of user/item cold start,and only models the item ratings by users,ignoring the information contained in the review ...
FANG Yi-qiu, ZHANG Zhen-kun, GE Jun-wei
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Advances and Perspectives on Knowledge Transfer Based Cross-Domain Recom-mendation
Jisuanji kexue yu tansuo, 2020 Data sparseness and cold start problems caused by unbalanced data distribution restrict the further development of personalized recommendation systems. With the rise of transfer learning technology, cross-domain recommendation based on transfer learning ...
REN Hao, LIU Baisong, SUN Jinyang
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Data Science and Engineering, 2023 Cross-domain recommendation (CDR) has become an important research direction in the field of recommender systems due to the increasing demand for personalized recommendations across different domains.
Shuo Xiao +3 more
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Exploiting high-order behaviour patterns for cross-domain sequential recommendation
Connection Science, 2022 The cross-domain sequential recommendation aims to predict the next item based on a sequence of recorded user behaviours in multiple domains. We propose a novel Cross-domain Sequential Recommendation approach with Graph-Collaborative Filtering (CsrGCF ...
Bingyuan Wang +6 more
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Cross-domain Recommendation Model Based on SVD++ and Tag [PDF]
Jisuanji gongcheng, 2018 Currently,most cross-domain recommendation models have two problems:the prediction error becomes large when the user fails to add a tag to the specified item and when building the model,the user’s history label is not taken into account,which causes the ...
XING Changzheng,YANG Xiaoting
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A CCA-Based Item-Side Alignment Method for Cross-Domain Recommendation System
IEEE Access, 2021 For cross-domain recommendation, it can be divided into strong correlation and weak correlation problems according to the consistency between auxiliary domain and target domain.
Lanting Wang, Yu Xin
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Cross-domain recommendation model of deep feature extraction and attention mechanism
Shenzhen Daxue xuebao. Ligong ban, 2023 To alleviate the problem of sparse target domain data and cold start in cross domain recommendation, Cross-domain recommendation model of deep feature extraction and attention mechanism (CRDFEAM) model is proposed by combining the techniques including ...
CAO Fengping, ZHANG Ruiting
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Review of Embedding Methods and Domain Alignment Techniques in Dual-Target Cross-Domain Recommendation [PDF]
Jisuanji kexue yu tansuoAs a key branch of cross-domain recommendation technology, dual-target cross-domain recommendation improves the efficiency of source domain and target domain recommendation synchronously by virtue of a two-way collaborative optimization mechanism, and is
HU Siyu, MEI Hongyan, YANG Haiyan, CHENG Nai, ZHANG Xiaoyu
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Leveraging Transitive Trust Relations to Improve Cross-Domain Recommendation
IEEE Access, 2018 Cross-domain recommendation has become increasingly popular because it can determine dependencies and correlations among different domains. However, this type of recommendation still suffers from data sparsity limitations. Social trust relationship helps
Guofang Ma +3 more
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