为了方便查看与了解,我们主要将其分为了以下几类:Sequential RS,Graph-based RS,Cold-start in RS,Efficient RS,Knowledge-aware RS...分类 数量 Sequential RS 8 Graph-based RS 6 Robust RS 6 Efficient RS 5 Knowledge-aware RS 5 Cold-start in...Cold-start RS Content-aware Neural Hashing for Cold-start Recommendation....Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste....CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network.
in Recommender System Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction...【学习图元嵌入表示】 FORM: Follow the Online Regularized Meta-Leader for Cold-Start Recommendation【在线正则化的元学习器】...for Cold-start Recommendation with Meta Scaling and Shifting Networks【如何warm up】 Fairness among New...Users【short paper】 Cluster-Based Bandits: Fast Cold-Start for Recommender System New Users【short paper...,基于聚类的老虎机模型来快速冷启动】 Sequential Recommendation for Cold-start Users with Meta Transitional Learning【short
1 融合邻居节点预训练表示 Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction(SIGIR...Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation(WSDM 2021)中也提出了类似的方法...Hers: Modeling influential contexts with heterogeneous relations for sparse and cold-start recommendation...例如在GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction(CIKM 2022)这篇文章中...Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation(WSDM 2021)中通过也引入了user
[2] Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings...IJCAI2017. [6] Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users....KDD2021. [9] A Meta-Learning Perspective on Cold-Start Recommendations for Items....NeurIPS2017. [10] MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation....KDD2019. [11] Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation.
warm start实验,也就是基于这个映射得到向量表示作为初始化,使用后续交互数据微调,得到以下结果,可以看到,针对warm start场景,我们的方法也是很有效的,这也是第一篇同时验证跨领域推荐方法在cold-start...Semi-supervised learning for cross-domain recommendation to cold-start users[C]// CIKM: 1563-1572. [3...Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users[C]....Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting
本文基于SIGIR-2021论文《Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling...在这篇文章中,我们将冷启动问题划分为两个阶段,cold-start阶段和warm-up阶段,cold-start阶段表示完全没有样本的情况,而warm-up阶段表示有少量样本的情况。...Warm up cold-start advertisements: Improving ctr predictions via learning to learn id embeddings[C]//...MeLU: meta-learned user preference estimator for cold-start recommendation[C]//Proceedings of the 25th
Simulation Counterfactual Review-based Recommendation Reinforcement Learning to Optimize Lifetime Value in Cold-Start...Recommendation Zero Shot on the Cold-Start Problem: Model-Agnostic Interest Learning for Recommender...Meta-learning Model for Session-based Recommendation CMML: Contextual Modulation Meta Learning for Cold-Start
Geography-Aware Sequential Location Recommendation 【Microsoft】 论文:staff.ustc.edu.cn/~lian Cold-Start...MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation 论文:arxiv.org/abs/2007.0318 2....Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation 论文:https://ink.library.smu.edu.sg
AutoML-based Others 3 按照研究话题划分 Bias/Debias in Recommender System Explanation in Recommender System Long-tail/Cold-start...in Recommender System Socially-aware Dual Contrastive Learning for Cold-Start Recommendation 【short...paper,社交感知的双重对比学习】 Transform Cold-Start Users into Warm via Fused Behaviors in Large-Scale Recommendation...【short paper,通过融合行为转换冷启动用户】 Generative Adversarial Framework for Cold-Start Item Recommendation 【short...paper,针对冷启动商品的生成对抗框架】 Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational
A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations Krishna P Neupane, Ervine...SMINet: State-Aware Multi-Aspect Interests Representation Network for Cold-Start Users Recommendation
第二篇文章是Learning to warm up cold item embeddings for cold-start recommendation with meta scaling and shifting...在今年的SIGIR上,Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder...3 基于对比学习学习embedding 基于对比学习学习embedding的典型工作是Contrastive learning for cold-start recommendation(Multimedia...4 根据用户历史行为生成embedding 在今年SIGIR 2022中阿里发表了一篇文章Transform Cold-Start Users into Warm via Fused Behaviors
雷锋网 AI 科技评论按:7 月 9 日,自然语言处理顶会 ACL 公布了最佳 demo 论文的四篇候选论文,名单如下: CRUISE: Cold-Start New Skill Development...最佳 demo 论文 CRUISE: Cold-Start New Skill Development via Iterative Utterance Generation CRUISE:基于迭代语料生成的冷启动新技能开发
A Preference Learning Decoupling Framework for User Cold-Start Recommendation Chunyang Wang, Yanmin Zhu...Model-agnostic Behavioral Distillation For Cold-start Item Recommendation Zefan Wang, Hao Chen, Xiao...M2EU: Meta Learning for Cold-start Recommendation via Enhancing User Preference Estimation Zhenchao Wu...Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation Taichi Liu, Chen Gao, Zhenyu...TAML: Time-Aware Meta Learning for Cold-Start Problem in News Recommendation Jingyuan Li, Yue Zhang,
Imbalanced Recommendation【GRP:基于 Gumbel 的不平衡推荐评级预测框架】 Generative Adversarial Zero-Shot Learning for Cold-Start...Contrastive Learning Framework for Sequential Recommendation【序列推荐的多层次对比学习框架】 Multimodal Meta-Learning for Cold-Start...User Recommendation in Social Metaverse with VR【VR的用户推荐】 点击率估计 GIFT: Graph-guIded Feature Transfer for Cold-Start
Prediction Framework for Imbalanced Recommendation Generative Adversarial Zero-Shot Learning for Cold-Start...Multi-Faceted Hierarchical Multi-Task Learning for Recommender Systems Multimodal Meta-Learning for Cold-Start
第二篇文章是MeLU: meta-learned user preference estimator for cold-start recommendation(KDD 2019)。...Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction(SIGIR 2021)利用图学习解决新
CoMeta: Enhancing Meta Embeddings with Collaborative Information in Cold-start Problem of Recommendation...CoMeta: Enhancing Meta Embeddings with Collaborative Information in Cold-start Problem of Recommendation...Haonan Hu, Dazhong Rong, Jianhai Chen, Qinming He, Zhenguang Liu https://arxiv.org/abs/2303.07607 The cold-start...Some recent studies introduce meta learning to solve the cold-start problem by generating meta embeddings
ColdNAS: Search to Modulate for User Cold-Start Recommendation 9....ColdNAS: Search to Modulate for User Cold-Start Recommendation Shiguang Wu, Yaqing Wang, Qinghe Jing,...Dong, Dejing Dou, Quanming Yao https://arxiv.org/abs/2306.03387 Making personalized recommendation for cold-start...deciding modulation position by expertise, we propose a modulation framework called ColdNAS for user cold-start...that JGCF is better at handling sparse datasets, which shows potential in making recommendations for cold-start
IJCAI2017. [3] Semi-supervised learning for cross-domain recommendation to cold-start users....CIKM2019. [4] Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users.
Learning Informative Priors from Heterogeneous Domains to Improve Recommendation in Cold-Start User Domains...A deep multimodal approach for cold-start music recommendation. arXiv preprint arXiv:1706.09739.
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