add GraphRS survey

cubean · Apr 28, 2020 · f8f0662 · f8f0662
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diff --git a/...-Adversarial Multimodal Representation Learning for Click-Through Rate Prediction-WWW.pdf b/...-Adversarial Multimodal Representation Learning for Click-Through Rate Prediction-WWW.pdf
diff --git a/...ure Data Helps Training-Modeling Future Contexts for Session-based Recommendation-WWW.pdf b/...ure Data Helps Training-Modeling Future Contexts for Session-based Recommendation-WWW.pdf
diff --git a/01-Surveys/2019-A survey on group recommender systems..pdf b/01-Surveys/2019-A survey on group recommender systems..pdf
diff --git a/01-Surveys/2020-Graph Learning Approaches to Recommender Systems-A Review.pdf b/01-Surveys/2020-Graph Learning Approaches to Recommender Systems-A Review.pdf
diff --git a/...14-TopicMF-Simultaneously Exploiting Ratings and Reviews for Recommendation-AAAI-Yang.pdf b/...14-TopicMF-Simultaneously Exploiting Ratings and Reviews for Recommendation-AAAI-Yang.pdf
diff --git a/README.md b/README.md
@@ -81,12 +81,13 @@ the user with the recommendations, but also make the user aware why such items a
 
 * Zhu et al. **Research Commentary on Recommendations with Side Information: A Survey and Research Directions.**  Electron. Commer. Res. Appl., 2019.
 
+* Sriharsha et al. **A Survey on Group Recommender Systems.** J. Intell. Inf. Syst., 2019.
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 * Dietmar et al. **A Survey on Conversational Recommender Systems.** arXiv, 2020.
 
 * Qingyu et al. **A Survey on Knowledge Graph-Based Recommender Systems.** arXiv, 2020.
 
-* Sriharsha et al. **A Survey on Group Recommender Systems.** J. Intell. Inf. Syst., 2020
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+* Wang et al. **Graph Learning Approaches to Recommender Systems: A Review.** arXiv, 2020.
 
 
 ## General Recommender System
@@ -145,6 +146,8 @@ the user with the recommendations, but also make the user aware why such items a
 
 * Hernández-Lobato et al. **Probabilistic matrix factorization with non-random missing data.** ICML, 2014.
 
+* Yang et al. **TopicMF: Simultaneously Exploiting Ratings and Reviews for Recommendation.** AAAI, 2014.
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 * Shi et al. **Semantic path based personalized recommendation on weighted heterogeneous information networks.** CIKM, 2015.
 
 * Grbovic et al. **E-commerce in your inbox: Product recommendations at scale.** KDD, 2015.