Neural Feature-aware Recommendation with Signed Hypergraph Convolutional Network

Understanding user preference is of key importance for an effective recommender system. For comprehensive user profiling, many efforts have been devoted to extract user feature-level preference fro...

[1]  Yongfeng Zhang,et al.  Reinforcement Knowledge Graph Reasoning for Explainable Recommendation , 2019, SIGIR.

[2]  Tao Chen,et al.  TriRank: Review-aware Explainable Recommendation by Modeling Aspects , 2015, CIKM.

[3]  Guokun Lai,et al.  Explicit factor models for explainable recommendation based on phrase-level sentiment analysis , 2014, SIGIR.

[4]  William W. Cohen,et al.  TransNets: Learning to Transform for Recommendation , 2017, RecSys.

[5]  Yongfeng Zhang,et al.  Personalized Key Frame Recommendation , 2017, SIGIR.

[6]  Yuan He,et al.  Graph Neural Networks for Social Recommendation , 2019, WWW.

[7]  Deng Cai,et al.  Heterogeneous hypergraph embedding for document recommendation , 2016, Neurocomputing.

[8]  Yongfeng Zhang,et al.  Towards Controllable Explanation Generation for Recommender Systems via Neural Template , 2020, WWW.

[9]  Song Bai,et al.  Hypergraph Convolution and Hypergraph Attention , 2019, Pattern Recognit..

[10]  Tat-Seng Chua,et al.  Neural Collaborative Filtering , 2017, WWW.

[11]  Yu Fan,et al.  KERL: A Knowledge-Guided Reinforcement Learning Model for Sequential Recommendation , 2020, SIGIR.

[12]  Abhinav Gupta,et al.  Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[13]  Yue Yin,et al.  Explainable Recommendation via Multi-Task Learning in Opinionated Text Data , 2018, SIGIR.

[14]  Le Wu,et al.  A Neural Influence Diffusion Model for Social Recommendation , 2019, SIGIR.

[15]  Minyi Guo,et al.  SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction , 2017, WSDM.

[16]  Yongfeng Zhang,et al.  Incorporating Phrase-level Sentiment Analysis on Textual Reviews for Personalized Recommendation , 2015, WSDM.

[17]  Yue Gao,et al.  Hypergraph Neural Networks , 2018, AAAI.

[18]  Siu Cheung Hui,et al.  Multi-Pointer Co-Attention Networks for Recommendation , 2018, KDD.

[19]  Xing Xie,et al.  Session-based Recommendation with Graph Neural Networks , 2018, AAAI.

[20]  Changsheng Xu,et al.  A Unified Personalized Video Recommendation via Dynamic Recurrent Neural Networks , 2017, ACM Multimedia.

[21]  Yongfeng Zhang,et al.  Dynamic Explainable Recommendation Based on Neural Attentive Models , 2019, AAAI.

[22]  Nicholas Jing Yuan,et al.  DRN: A Deep Reinforcement Learning Framework for News Recommendation , 2018, WWW.

[23]  Jure Leskovec,et al.  Graph Convolutional Neural Networks for Web-Scale Recommender Systems , 2018, KDD.

[24]  Xiaohui Yu,et al.  Modeling and Predicting the Helpfulness of Online Reviews , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[25]  Jiliang Tang,et al.  Signed Graph Convolutional Networks , 2018, 2018 IEEE International Conference on Data Mining (ICDM).

[26]  Xu Chen,et al.  Learning to Rank Features for Recommendation over Multiple Categories , 2016, SIGIR.

[27]  Jure Leskovec,et al.  Hidden factors and hidden topics: understanding rating dimensions with review text , 2013, RecSys.

[28]  Li Peng,et al.  A Capsule Network for Recommendation and Explaining What You Like and Dislike , 2019, SIGIR.

[29]  Jing Huang,et al.  Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction , 2017, RecSys.

[30]  Tat-Seng Chua,et al.  Neural Graph Collaborative Filtering , 2019, SIGIR.

[31]  Korris Fu-Lai Chung,et al.  A Deep Bayesian Tensor-Based System for Video Recommendation , 2018, ACM Trans. Inf. Syst..

[32]  Chengjiang Li,et al.  Multi-Channel Graph Neural Network for Entity Alignment , 2019, ACL.

[33]  Yongfeng Zhang,et al.  Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network: Towards Visually Explainable Recommendation , 2019, SIGIR.

[34]  Li Chen,et al.  Generate Neural Template Explanations for Recommendation , 2020, CIKM.

[35]  Yang Liu,et al.  Neural Attention Frameworks for Explainable Recommendation , 2021, IEEE Transactions on Knowledge and Data Engineering.

[36]  Yiqun Liu,et al.  Neural Attentional Rating Regression with Review-level Explanations , 2018, WWW.

[37]  Jie Zhang,et al.  A Re-visit of the Popularity Baseline in Recommender Systems , 2020, SIGIR.

[38]  Jun Chang,et al.  DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation , 2019, KDD.

[39]  Yixin Cao,et al.  Explainable Reasoning over Knowledge Graphs for Recommendation , 2018, AAAI.

[40]  Prateek Yadav,et al.  HyperGCN: Hypergraph Convolutional Networks for Semi-Supervised Classification , 2018, ArXiv.