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KDD2019

链接：KDD2019

1. An Visual Dialog Augmented Interactive Recommender System
2. Coupled Variational Recurrent Collaborative Filtering
3. Enhancing Collaborative Filtering with Generative Augmentation
4. MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation
5. Infer Implicit Contexts in Real-time Online-to-Offline Recommendation
6. Real-time Attention Based Look-alike Model for Recommender System
7. A Deep Generative Approach to Search Extrapolation and Recommendation
8. Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction
9. DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation
10. DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview
11. Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search
12. Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System
13. NPA: Neural News Recommendation with Personalized Attention
14. Oboe: Collaborative Filtering for AutoML Model Selection
15. POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion
16. Social Recommendation with Optimal Limited Attention
17. Streaming Session-based Recommendation
18. Topic-Enhanced Memory Networks for Personalised Point-of-Interest Recommendation

KDD2018

链接：KDD2018

1. Neural Memory Streaming Recommender Networks with Adversarial Training
2. Stablizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation
3. Graph Convolutional Neural Networks for Web-Scale Recommender Systems
4. Learning Tree-based Deep Model for Recommender Systems
5. Leveraging Meta-path based Context for Top-N Recommendation with A Neural Co-Attention Model
6. Multi-Pointer Co-Attention Networks for Recommendation

KDD2017

1. Collaborative Variational Autoencoder for Recommender Systems

KDD2015

1. Collaborative Deep Learning for Recommender Systems

WWW2019

1. Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
2. Signed Distance-based Deep Memory Recommender
3. Multimodal Review Generation for Recommender Systems
4. Graph Neural Networks for Social Recommendation
5. Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
6. Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preference
7. Hierarchical Temporal Convolutional Networks for Dynamic Recommender Systems
8. NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization
9. GhostLink: Latent Network Inference for Influence-aware Recommendation
10. Dual Graph A�ention Networks for Deep Latent Representation of Multifaceted Social E�ects in Recommender Systems

WWW2018

1. DRN: A Deep Reinforcement Learning Frameworkfor News Recommendation
2. Coevolutionary Recommendation Model: MutualLearning between Rating and Reviews
3. TEM: Tree-enhanced Embedding Model for Explainable Recommendation
4. Variational Autoencoders for Collaborative Filtering

WWW2017

1. Neural Collaborative Filtering

RecSys2019

1. A pareto-efficient algorithm for multiple objective optimization in e-commerce recommendation
2. CB2CF: a neural multiview content-to-collaborative filtering model for completely cold item recommendations
3. AreWe Really Making Much Progress? AWorrying Analysis of Recent Neural Recommendation Approaches

RecSys2018

1. Spectral Collaborative Filtering
2. Recurrent Knowledge Graph Embedding for Effective Recommendation
3. Attentive Neural Architecture Incorporating Song Features for Music Recommendation
4. Deep neural network marketplace recommenders in online experiments

SIGIR2019

链接：SIGIR2019

1. Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation
2. ReinforcementLearning for User Intent Prediction in Customer Service Bots
3. A Capsule Network for Recommendation and Explaining What You Like and Dislike
4. Neural Graph Collaborative Filtering
5. Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
6. Transparent, Scrutable and Explainable User Models for Personalized Recommendation
7. SAIN: Self-Attentive Integration Network for Recommendation

SIGIR2018

1. Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks
2. Collaborative Memory Network for Recommendation Systems
3. A Contextual Attention Recurrent Architecture for Context-Aware Venue Recommendation
4. Adversarial Personalized Ranking for Recommendation

SIGIR2017

1. Attentive Collaborative Filtering: Multimedia Recommendation with Item-and Component-Level Attention