NeuRec is a comprehensive and flexible Python library for recommender systems that includes a large range of state-of-the-art neural recommender models. This library aims to solve general, social and sequential (i.e. next-item) recommendation tasks, using the
Tensorflow library to provide 33 models out of the box. NeuRec is open source and available under the MIT license.
The list of available models in NeuRec, along with their paper citations, are shown below:
General Recommender Paper GMF, MLP, NeuMF Xiangnan He et al., Neural Collaborative Filtering , WWW 2017. BPRMF Steffen Rendle et al., BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI 2009. FISM Santosh Kabbur et al., FISM: Factored Item Similarity Models for Top-N Recommender Systems. KDD 2013. NAIS Xiangnan He et al., NAIS: Neural Attentive Item Similarity Model for Recommendation . TKDE2018. DeepICF Feng Xue et al., Deep Item-based Collaborative Filtering for Top-N Recommendation. TOIS 2019. ConvNCF Xiangnan He et al., Outer Product-based Neural Collaborative Filtering . IJCAI 2018. DMF Hong-Jian Xue et al., Deep Matrix Factorization Models for Recommender Systems. IJCAI 2017. CDAE, DAE Yao Wu et al., Collaborative denoising auto-encoders for top-n recommender systems. WSDM 2016. MultiDAE, MultiVAE Dawen Liang, et al., Variational autoencoders for collaborative filtering. WWW 2018. JCA Ziwei Zhu, et al., Improving Top-K Recommendation via Joint Collaborative Autoencoders. WWW 2019. IRGAN Jun Wang, et al., IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models. SIGIR 2017. CFGAN Dong-Kyu Chae, et al., CFGAN: A Generic Collaborative Filtering Framework based on Generative Adversarial Networks. CIKM 2018. APR Xiangnan He, et al., Adversarial Personalized Ranking for Recommendation. SIGIR 2018. SpectralCF Lei Zheng, et al., Spectral Collaborative Filtering. RecSys 2018. NGCF Xiang Wang, et al., Neural Graph Collaborative Filtering. SIGIR 2019. WRMF Yifan Hu, et al., Collaborative Filtering for Implicit Feedback Datasets. ICDM 2008.
Social Recommender Paper SBPR Tong Zhao et al., Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering. CIKM 2014. DiffNet Le Wu et al., A Neural Influence Diffusion Model for Social Recommendation, SIGIR 2019.
Sequential Recommender Paper FPMC, FPMCplus Steffen Rendle et al., Factorizing Personalized Markov Chains for Next-Basket Recommendation, WWW 2010. HRM Pengfei Wang et al., Learning Hierarchical Representation Model for NextBasket Recommendation, SIGIR 2015. NPE ThaiBinh Nguyen et al., NPE: Neural Personalized Embedding for Collaborative Filtering, ijcai 2018. TransRec Ruining He et al., Translation-based Recommendation, SIGIR 2015. Caser Jiaxi Tang et al., Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding, WSDM 2018. Fossil Ruining He et al., Fusing similarity models with Markov chains for sparse sequential recommendation, ICDM 2016. GRU4Rec Balázs Hidasi et al., Session-based Recommendations with Recurrent Neural Networks, ICLR 2016. GRU4RecPlus Balázs Hidasi et al., Recurrent Neural Networks with Top-k Gains for Session-based Recommendations, CIKM 2018. SASRec Wangcheng Kang et al., Self-Attentive Sequential Recommendation, ICDM 2018. SRGNN Shu Wu et al., Session-Based Recommendation with Graph Neural Networks, AAAI 2019.