IJCAI19最新推薦系統論文分享

一年一度的AI盛會IJCAI將於2019年8月10日至16日在中國澳門舉行，在此特整理關於推薦系統方向最新的論文列表，希望對大家有所幫助。通過整理論文列表發現：
① 深度學習
技術應用於推薦系統領域依然保持火熱的勢頭。其中筆者嘗試通過搜索[deep]關鍵字，結果找到了92個相關項，可見深度學習作品星羅棋佈。② 關於推薦系統領域的研究多點開花，研究方向涉及社會化推薦、視頻推薦、可解釋性推薦、序列化/會話推薦、POI推薦以及異構信息網路上的推薦、跨域推薦等。

③ 推薦系統領域知名學者依然保持高產。其中微軟亞研院的謝幸老師6篇，新加坡國立大學
的何向南老師5篇，東北大學的郭貴冰老師2篇。另外，Irwin King，Jiliang Tang等大佬也有論文入選。總之希望有越來越多的推薦系統大佬能夠出現在此行列。

社會化推薦

Wenqi et al. Deep Adversarial Social Recommendation.
Guibing et al. Discrete Trust-aware Matrix Factorization for Fast Recommendation.
Federico et al. Recommending Links to Maximize the Influence in Social Networks.
Qitian Wu et al. Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust.
Yongji et al. Graph Convolutional Networks on User Mobility Heterogeneous Graphs for Social Relationship Inference.

深度學習推薦

Zeping et al. Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommendation.
Dong Xi et al. BPAM: Recommendation Based on BP Neural Network with Attention Mechanism.
Xin et al. CFM: Convolutional Factorization Machines for Context-Aware Recommendation.
Xiao Zhou et al. Collaborative Metric Learning with Memory Network for Multi-Relational Recommender Systems.
Junyang et al. Convolutional Gaussian Embeddings for Personalized Recommendation with Uncertainty.
Liang et al. Matching User with Item Set: Collaborative Bundle Recommendation with Attention Network.
Chuhan et al. Neural News Recommendation with Attentive Multi-View Learning.
Qiong et al. PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation.
Jiani et al. STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems.

可解釋性推薦

Zhongxia et al. Co-Attentive Multi-Task Learning for Explainable Recommendation.
Min et al. Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach.

序列/會話推薦

Guibing et al. Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation.
Tingting et al. Feature-level Deeper Self-Attention Network for Sequential Recommendation.
Chengfeng et al. Graph Contextualized Self-Attention Network for Session-based Recommendation.
Yejin et al. Sequential and Diverse Recommendation with Long Tail.
Jing Song et al. ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation.
Shoujin et al. Sequential Recommender Systems: Challenges, Progress and Prospects.
Chenliang et al. A Review-Driven Neural Model for Sequential Recommendation.

視頻推薦

Huan et al. DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation.
Shengze et al. Disparity-preserved Deep Cross-platform Association for Cross-platform Video Recommendation.
Jia et al. Multi-View Active Learning for Video Recommendation.

異質信息網路推薦

Yanan et al. Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation.
Zekai et al. Unified Embedding Model over Heterogeneous Information Network for Personalized Recommendation.