跨域推荐(Cross-domain recommendation, CDR)是利用其他域的辅助用户行为来缓解数据稀疏性问题的代表性方法之一[24,53]。经典的CDR方法一般采用多任务学习[52]、对齐约束[20,35]和对比学习[41]对跨领域知识迁移进行建模。跨域顺序推荐(CDSR)更多关注用户在CDR中的多域时间顺序行为[2,3,10,17,39,46]。DASL[17]...
Recently, various cross-domain recommendation (CDR) models are proposed to overcome the sparsity problem, which leverage relatively abundant rating data from the auxiliary domain to improve recommendation performance of target domain. Though matrix factorization-based collaborative filtering algorithms gain ...
Sequential CDR,sequential recommendation 在购物推荐等领域取得了很好的效果,如何对这个任务做 cross-domain Privacy-Preserving CDR,现有的 CDR 任务都假设不同域之间可以看到全部信息,实际上真实情况中可能不能直接获取到 Comments 文章写的很浅,只做了罗列,没有深入的梳理方法发展的脉络,不过目前也没有其他以 cross-...
然而,匹配(matching,即候选生成)模块中的CDR在知识迁移和表征学习上受数据稀疏性和流行度偏差的影响。本文提出了一种对比跨域推荐 (CCDR) 框架,用于CDR中的匹配。具体来说,我们构建了一个巨大的多元化偏好网络来捕获反映用户不同兴趣的多种信息,并设计了一个域内对比学习(intra-CL)和三个域间对比学习(inter-CL)...
Cross-Domain Recommendation (CDR) aims to solve data sparsity and cold-start problems by utilizing a relatively information-rich source domain to improve the recommendation performance of the data-sparse target domain. However, most existing approaches rely on the assumption of centralized storage of ...
5.4Potential Limitations of Domain Quantity 一、Abstrct 随着人们不可避免地跨越多个领域或各种平台与物品进行交互,跨领域推荐( Cross-domain Recommendation,CDR )得到了越来越多的关注。然而,日益增长的隐私问题限制了现有CDR模型的实际应用,因为它们假设不同领域之间的全部或部分数据是可访问的。
DisenCDR: learning disentangled representations for cross-domain recommendation. In ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022.概本文针对的是跨域的学习, 希望解耦出 domain-specific 特征和共享特征. 思路倒是没有特别新, 但是这个操作感觉是个大工程啊....
Thus, on the basis of UL and attentive GCCF, this paper proposes a Cross-domain Recommendation for e-commerce using User-level Preferences Transfer Network (CDR-ULPT). Experiments are conducted on public datasets. The experiments demonstrate the effectiveness of the proposed model. The distinct con...
内容提示: Federated Graph Learning for Cross-DomainRecommendationZiqi Yang 1,2 , Zhaopeng Peng 1,2 , Zihui Wang 1,2 , Jianzhong Qi 3 , Chaochao Chen 4 ,Weike Pan 5 , Chenglu Wen 1,2 , Cheng Wang 1,2 , Xiaoliang Fan 1,2 ∗1 Fujian Key Laboratory of Sensing and Computing for ...
AMT-CDR: A Deep Adversarial Multi-channel Transfer Network for Cross-domain Recommendation recommender-systemcross-domain-recommendation UpdatedNov 2, 2023 Python Enhanced recommendations through sentiment analysis on reviews and prioritized popular attractions based on keyword frequency, ensuring more personaliz...