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          "authors": "Chong Chen, Min Zhang, YongFeng Zhang, YiQun Liu and ShaoPing Ma",
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          "paper_link": "https://doi.org/10.1145/2487575.2487589",
          "authors": "Santosh Kabbur, Xia Ning and George Karypis",
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          "paper": "Graph Convolutional Matrix Completion",
          "paper_link": "http://arxiv.org/abs/1706.02263",
          "authors": "Rianne van den Berg, Thomas N. Kipf and Max Welling",
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          "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
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          "paper": "Efficient Top-N Recommendation for Very Large Scale Binary Rated Datasets",
          "paper_link": "https://doi.org/10.1145/2507157.2507189",
          "authors": "Fabio Aiolli",
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          "pub": "SIGIR'20",
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          "paper": "LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation",
          "paper_link": "https://doi.org/10.1145/3397271.3401063",
          "authors": "Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, YongDong Zhang and Meng Wang",
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          "pub": "WWW'15",
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          "paper": "LINE: Large-scale Information Network Embedding",
          "paper_link": "https://doi.org/10.1145/2736277.2741093",
          "authors": "Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan and Qiaozhu Mei",
          "ref_code": "https://github.com/shenweichen/GraphEmbedding",
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          "pub": "NIPS'19",
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          "paper": "Learning disentangled representations for recommendation",
          "paper_link": "https://dl.acm.org/doi/10.5555/3454287.3454800",
          "authors": "Jianxin Ma, Chang Zhou, Peng Cui, Hongxia Yang and Wenwu Zhu",
          "ref_code": "https://jianxinma.github.io/disentangle-recsys.html",
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          "pub": "WWW'18",
          "model": "MultiDAE",
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          "paper": "Variational Autoencoders for Collaborative Filtering",
          "paper_link": "https://doi.org/10.1145/3178876.3186150",
          "authors": "Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman and Tony Jebara",
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          "pub": "WWW'18",
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          "paper": "Variational Autoencoders for Collaborative Filtering",
          "paper_link": "https://doi.org/10.1145/3178876.3186150",
          "authors": "Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman and Tony Jebara",
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          "year": "2018",
          "pub": "TKDE'18",
          "model": "NAIS",
          "model_link": "/docs/user_guide/model/general/nais.html",
          "paper": "NAIS: Neural Attentive Item Similarity Model for Recommendation",
          "paper_link": "http://arxiv.org/abs/1809.07053",
          "authors": "Xiangnan He, Zhankui He, Jingkuan Song, Zhenguang Liu, Yu-Gang Jiang and Tat-Seng Chua",
          "ref_code": "https://github.com/AaronHeee/Neural-Attentive-Item-Similarity-Model",
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          "pub": "SIGIR'19",
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          "paper": "Noise Contrastive Estimation for One-Class Collaborative Filtering",
          "paper_link": "https://dl.acm.org/doi/epdf/10.1145/3331184.3331201",
          "authors": "Ga Wu, Maksims Volkovs, Chee Loong Soon, Scott Sanner and Himanshu Rai",
          "ref_code": "https://github.com/wuga214/NCE_Projected_LRec",
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          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "category": "General Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
          "year": "2022",
          "pub": "WWW'22",
          "model": "NCL",
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          "paper": "Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning",
          "paper_link": "http://arxiv.org/abs/2202.06200v2",
          "authors": "Zihan Lin, Changxin Tian, Yupeng Hou and Wayne Xin Zhao",
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          "pub": "WWW'17",
          "model": "NeuMF",
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          "paper": "Neural Collaborative Filtering",
          "paper_link": "http://dl.acm.org/doi/pdf/10.1145/3038912.3052569",
          "authors": "Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu and Tat-Seng Chua",
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          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "pub": "SIGIR'19",
          "model": "NGCF",
          "model_link": "/docs/user_guide/model/general/ngcf.html",
          "paper": "Neural Graph Collaborative Filtering",
          "paper_link": "http://dl.acm.org/doi/pdf/10.1145/3331184.3331267",
          "authors": "Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng and Tat-Seng Chua",
          "ref_code": "https://github.com/xiangwang1223/neural_graph_collaborative_filtering",
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          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "year": "2017",
          "pub": "CIKM'17",
          "model": "NNCF",
          "model_link": "/docs/user_guide/model/general/nncf.html",
          "paper": "A Neural Collaborative Filtering Model with Interaction-based Neighborhood",
          "paper_link": "http://dl.acm.org/doi/pdf/10.1145/3132847.3133083",
          "authors": "Ting Bai, Ji-Rong Wen, Jun Zhang and Wayne Xin Zhao",
          "ref_code": "https://github.com/Tbbaby/NNCF-Pytorch",
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          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
          "year": "2020",
          "pub": "ICLR'20",
          "model": "RaCT",
          "model_link": "/docs/user_guide/model/general/ract.html",
          "paper": "Towards Amortized Ranking-Critical Training for Collaborative Filtering",
          "paper_link": "https://arxiv.org/abs/1906.04281",
          "authors": "Sam Lobel, Chunyuan Li, Jianfeng Gao and Lawrence Carin",
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          "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
          "year": "2020",
          "pub": "WSDM'20",
          "model": "RecVAE",
          "model_link": "/docs/user_guide/model/general/recvae.html",
          "paper": "RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback",
          "paper_link": "http://dl.acm.org/doi/epdf/10.1145/3336191.3371831",
          "authors": "Ilya Shenbin, Anton Alekseev, Elena Tutubalina, Valentin Malykh and Sergey I. Nikolenko",
          "ref_code": "https://github.com/ilya-shenbin/RecVAE",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "category": "General Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
          "year": "2021",
          "pub": "SIGIR'21",
          "model": "SGL",
          "model_link": "/docs/user_guide/model/general/sgl.html",
          "paper": "Self-supervised Graph Learning for Recommendation",
          "paper_link": "https://arxiv.org/abs/2010.10783v4",
          "authors": "Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian and Xing Xie",
          "ref_code": "https://github.com/wujcan/SGL",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "category": "General Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
          "year": "2021",
          "pub": "CIKM'21",
          "model": "SimpleX",
          "model_link": "/docs/user_guide/model/general/simplex.html",
          "paper": "SimpleX: A Simple and Strong Baseline for Collaborative Filtering",
          "paper_link": "https://doi.org/10.1145/3459637.3482297",
          "authors": "Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao and Xiuqiang He",
          "ref_code": "https://github.com/xue-pai/TwoToweRS",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "category": "General Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
          "year": "2011",
          "pub": "ICDM'11",
          "model": "SLIMElastic",
          "model_link": "/docs/user_guide/model/general/slimelastic.html",
          "paper": "SLIM: Sparse Linear Methods for Top-N Recommender Systems",
          "paper_link": "https://doi.org/10.1109/ICDM.2011.134",
          "authors": "Xia Ning and George Karypis",
          "ref_code": "https://github.com/KarypisLab/SLIM, https://github.com/MaurizioFD/RecSys2019_DeepLearning_Evaluation/blob/master/SLIM_ElasticNet/SLIMElasticNetRecommender.py",
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          "pub": "RecSys'18",
          "model": "SpectralCF",
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          "paper": "Spectral Collaborative Filtering",
          "paper_link": "https://arxiv.org/pdf/1808.10523.pdf",
          "authors": "Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang and Philip S. Yu",
          "ref_code": "https://github.com/lzheng21/SpectralCF",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "category": "Sequential Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#sequential-recommendation",
          "year": "2019",
          "pub": "CIKM'19",
          "model": "BERT4Rec",
          "model_link": "/docs/user_guide/model/sequential/bert4rec.html",
          "paper": "BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer",
          "paper_link": "https://doi.org/10.1145/3357384.3357895",
          "authors": "Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou and Peng Jiang",
          "ref_code": "https://github.com/FeiSun/BERT4Rec",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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      {
          "category": "Sequential Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#sequential-recommendation",
          "year": "2018",
          "pub": "WSDM'18",
          "model": "Caser",
          "model_link": "/docs/user_guide/model/sequential/caser.html",
          "paper": "Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding",
          "paper_link": "https://doi.org/10.1145/3357384.3357895",
          "authors": "Jiaxi Tang and Ke Wang",
          "ref_code": "https://github.com/graytowne/caser_pytorch",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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      {
          "category": "Sequential Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#sequential-recommendation",
          "year": "2022",
          "pub": "SIGIR'22",
          "model": "CORE",
          "model_link": "/docs/user_guide/model/sequential/core.html",
          "paper": "CORE: Simple and Effective Session-based Recommendation within Consistent Representation Space",
          "paper_link": "https://arxiv.org/abs/2204.11067",
          "authors": "Yupeng Hou, Binbin Hu, Zhiqiang Zhang and Wayne Xin Zhao",
          "ref_code": "https://github.com/RUCAIBox/CORE",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "cate_link": "/docs/user_guide/model_intro.html#sequential-recommendation",
          "year": "2019",
          "pub": "AAAI'19",
          "model": "DIEN",
          "model_link": "/docs/user_guide/model/sequential/dien.html",
          "paper": "Deep Interest Evolution Network for Click-Through Rate Prediction",
          "paper_link": "https://ojs.aaai.org/index.php/AAAI/article/view/4545",
          "authors": "Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu and Kun Gai",
          "ref_code": "https://github.com/mouna99/dien",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "cate_link": "/docs/user_guide/model_intro.html#sequential-recommendation",
          "year": "2018",
          "pub": "SIGKDD'18",
          "model": "DIN",
          "model_link": "/docs/user_guide/model/sequential/din.html",
          "paper": "Deep Interest Network for Click-Through Rate Prediction",
          "paper_link": "https://doi.org/10.1145/3219819.3219823",
          "authors": "Guorui Zhou, Xiaoqiang Zhu, Chenru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li and Kun Gai",
          "ref_code": "https://github.com/zhougr1993/DeepInterestNetwork/tree/master/din",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "category": "Sequential Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#sequential-recommendation",
          "year": "2019",
          "pub": "IJCAI'19",
          "model": "FDSA",
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          "authors": "Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou and Domonkos Tikk",
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          "authors": "Xinyan Fan, Zheng Liu, Jianxun Lian, Wayne Xin Zhao, Xing Xie and Ji-Rong Wen",
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          "authors": "Jing Li, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Tao Lian and Jun Ma",
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          "authors": "Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose and Xiangnan He",
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          "pub": "IJCAI'18",
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          "paper": "NPE: Neural Personalized Embedding for Collaborative Filtering",
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          "authors": "ThaiBinh Nguyen and Atsuhiro Takasu",
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          "paper": "RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation",
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          "authors": "Pengjie Ren, Zhumin Chen, Jing Li, Zhaochun Ren, Jun Ma and Maarten de Rijke",
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          "paper": "S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization",
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          "authors": "Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang and Ji-Rong Wen",
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          "authors": "Wang-Cheng Kang and Julian McAuley",
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          "authors": "Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, Tat-Seng Chua",
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          "paper": "Sequential Recommender System based on Hierarchical Attention Network",
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          "authors": "Haochao Ying, Fuzhen Zhuang, Fuzheng Zhang, Yanchi Liu, Guandong Xu, Xing Xie, Hui Xiong and Jian Wu",
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          "paper": "Deep & Cross Network for Ad Click Predictions",
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          "authors": "Ruoxi Wang, Bin Fu, Gang Fu, Mingliang Wang",
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          "paper": "DCN V2: Improved Deep & Cross Network and Practical Lessons\nforWeb-scale Learning to Rank Systems",
          "paper_link": "https://dl.acm.org/doi/10.1145/3442381.3450078",
          "authors": "Ruoxi Wang, Rakesh Shivanna, Derek Z. Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi",
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          "authors": "Qiaoyu Tan, Jianwei Zhang, Jiangchao Yao, Ninghao Liu, Jingren Zhou, Hongxia Yang and Xia Hu",
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          "paper": "Deep Interest Evolution Network for Click-Through Rate Prediction",
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          "authors": "Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, Kun Gai",
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          "authors": "Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie and Tieniu Tan",
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          "paper": "Deep Interest Network for Click-Through Rate Prediction",
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          "authors": "Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, Kun Gai",
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          "paper": "Learning deep structured semantic models for web search using clickthrough data",
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          "pub": "WWW' 18",
          "model": "FwFM",
          "model_link": "/docs/user_guide/model/context/fwfm.html",
          "paper": "Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising",
          "paper_link": "https://dl.acm.org/doi/10.1145/3178876.3186040",
          "authors": "Junwei Pan, Jian Xu, Alfonso Lobos Ruiz, Wenliang Zhao, Shengjun Pan, Yu Sun, Quan Lu",
          "ref_code": "",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
      },
      {
          "category": "Context-aware Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#context-aware-recommendation",
          "year": "2007",
          "pub": "WWW' 07",
          "model": "LR",
          "model_link": "/docs/user_guide/model/context/lr.html",
          "paper": "Predicting Clicks Estimating the Click-Through Rate for New Ads",
          "paper_link": "https://dl.acm.org/doi/10.1145/1242572.1242643",
          "authors": "Matthew Richardson, Ewa Dominowska, Robert Ragno",
          "ref_code": "",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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      {
          "category": "Context-aware Recommendation",
          "cate_link": "/docs/user_guide/model_intro.html#context-aware-recommendation",
          "year": "2017",
          "pub": "SIGIR' 17",
          "model": "NFM",
          "model_link": "/docs/user_guide/model/context/nfm.html",
          "paper": "Neural Factorization Machines for Sparse Predictive Analytics",
          "paper_link": "https://dl.acm.org/doi/abs/10.1145/3077136.3080777",
          "authors": "Xiangnan He, Tat-Seng Chua",
          "ref_code": "",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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      {
          "category": "Context-aware Recommendation",
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          "year": "2016",
          "pub": "ICDM' 16",
          "model": "PNN",
          "model_link": "/docs/user_guide/model/context/pnn.html",
          "paper": "Product-based neural networks for user response prediction",
          "paper_link": "https://ieeexplore.ieee.org/abstract/document/7837964/",
          "authors": "Yanru Qu, Han Cai, Kan Ren, Weinan Zhang, Yong Yu, Ying Wen, Jun Wang",
          "ref_code": "",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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      {
          "category": "Context-aware Recommendation",
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          "year": "2016",
          "pub": "RecSys' 16",
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          "paper": "Wide & Deep Learning for Recommender Systems",
          "paper_link": "https://dl.acm.org/doi/10.1145/2988450.2988454",
          "authors": "Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah",
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          "category": "Context-aware Recommendation",
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          "year": "2018",
          "pub": "SIGKDD' 18",
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          "paper": "xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems",
          "paper_link": "https://dl.acm.org/doi/10.1145/3219819.3220023",
          "authors": "Jianxun Lian, Xiaohuan Zhou, Fuzheng Zhang, Zhongxia Chen, Xing Xie, Guangzhong Sun",
          "ref_code": "",
          "repository": "RecBole",
          "repo_link": "https://github.com/RUCAIBox/RecBole"
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            "pub": "CIKM' 19",
            "model": "FiGNN",
            "model_link": "/docs/user_guide/model/context/fignn.html",
            "paper": "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction",
            "paper_link": "https://dl.acm.org/doi/10.1145/3357384.3357951",
            "authors": "Zekun Li, Zeyu Cui, Shu Wu, Xiaoyu Zhang, Liang Wang",
            "ref_code": "https://github.com/CRIPAC-DIG/GraphCTR, https://github.com/xue-pai/FuxiCTR",
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            "repo_link": "https://github.com/RUCAIBox/RecBole"
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            "category": "Context-aware Recommendation",
            "cate_link": "/docs/user_guide/model_intro.html#context-aware-recommendation",
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            "pub": "WSDM' 23",
            "model": "KD_DAGFM",
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            "paper": "Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation",
            "paper_link": "https://arxiv.org/abs/2211.11159",
            "authors": "Zhen Tian, Ting Bai, Zibin Zhang, Zhiyuan Xu, Kangyi Lin, Ji-Rong Wen, Wayne Xin Zhao",
            "ref_code": "https://github.com/chenyuwuxin/DAGFM",
            "repository": "RecBole",
            "repo_link": "https://github.com/RUCAIBox/RecBole"
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          "category": "Data Augmentation",
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          "year": "2022",
          "pub": "ICDE'22",
          "model": "CL4SRec",
          "model_link": "https://github.com/RUCAIBox/RecBole-DA/blob/master/recbole/model/sequential_recommender/cl4srec.py",
          "paper": "Contrastive Learning for Sequential Recommendation",
          "paper_link": "https://ieeexplore.ieee.org/abstract/document/9835621",
          "authors": "Xu Xie, Fei Sun, Zhaoyang Liu, Shiwen Wu, Jinyang Gao, Jiandong Zhang, Bolin Ding and Bin Cui",
          "ref_code": "",
          "repository": "RecBole-DA",
          "repo_link": "https://github.com/RUCAIBox/RecBole-DA"
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      {
          "category": "Data Augmentation",
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          "year": "2022",
          "pub": "WSDM'22",
          "model": "DuoRec",
          "model_link": "https://github.com/RUCAIBox/RecBole-DA/blob/master/recbole/model/sequential_recommender/duorec.py",
          "paper": "Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation",
          "paper_link": "https://doi.org/10.1145/3488560.3498433",
          "authors": "Ruihong Qiu, Zi Huang, Hongzhi Yin and Zijian Wang",
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          "repository": "RecBole-DA",
          "repo_link": "https://github.com/RUCAIBox/RecBole-DA"
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          "category": "Data Augmentation",
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          "year": "2021",
          "pub": "ICDM'21",
          "model": "MMInfoRec",
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          "paper": "Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential Recommendation",
          "paper_link": "https://ieeexplore.ieee.org/abstract/document/9678990",
          "authors": "Ruihong Qiu, Zi Huang and Hongzhi Yin",
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          "repository": "RecBole-DA",
          "repo_link": "https://github.com/RUCAIBox/RecBole-DA"
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          "category": "Data Augmentation",
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          "year": "2021",
          "pub": "CIKM'21",
          "model": "CCL",
          "model_link": "https://github.com/RUCAIBox/RecBole-DA/tree/master/recbole/model/sequential_recommender/ccl",
          "paper": "Contrastive Curriculum Learning for Sequential User Behavior Modeling via Data Augmentation",
          "paper_link": "https://doi.org/10.1145/3459637.3481905",
          "authors": "Shuqing Bian, Wayne Xin Zhao, Kun Zhou, Jing Cai, Yancheng He, Cunxiang Yin and Ji-Rong Wen",
          "ref_code": "https://github.com/RUCAIBox/Contrastive-Curriculum-Learning",
          "repository": "RecBole-DA",
          "repo_link": "https://github.com/RUCAIBox/RecBole-DA"
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          "category": "Meta recommendation",
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          "year": "2019",
          "pub": "SIGKDD'19",
          "model": "MeLU",
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          "paper": "MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation",
          "paper_link": "https://doi.org/10.1145/3292500.3330859",
          "authors": "Hoyeop Lee, Jinbae Im, Seongwon Jang, Hyunsouk Cho and Sehee Chung",
          "ref_code": "https://github.com/hoyeoplee/MeLU",
          "repository": "RecBole-MetaRec",
          "repo_link": "https://github.com/nuster1128/RecBole-MetaRec"
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          "category": "Meta recommendation",
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          "year": "2020",
          "pub": "SIGKDD'20",
          "model": "MAMO",
          "model_link": "https://github.com/nuster1128/RecBole-MetaRec/blob/master/recbole_metarec/model/MAMO",
          "paper": "MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation",
          "paper_link": "https://doi.org/10.1145/3394486.3403113",
          "authors": "Manqing Dong, Feng Yuan, Lina Yao, Xiwei Xu and Liming Zhu",
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          "repository": "RecBole-MetaRec",
          "repo_link": "https://github.com/nuster1128/RecBole-MetaRec"
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          "year": "2021",
          "pub": "WWW'21",
          "model": "TaNP",
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          "paper": "Task-adaptive Neural Process for User Cold-Start Recommendation",
          "paper_link": "https://doi.org/10.1145/3442381.3449908",
          "authors": "Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao and Bin Wang",
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          "repository": "RecBole-MetaRec",
          "repo_link": "https://github.com/nuster1128/RecBole-MetaRec"
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          "year": "2017",
          "pub": "NIPS'17",
          "model": "LWA",
          "model_link": "https://github.com/nuster1128/RecBole-MetaRec/blob/master/recbole_metarec/model/LWA",
          "paper": "A Meta-Learning Perspective on Cold-Start Recommendations for Items",
          "paper_link": "https://proceedings.neurips.cc/paper/2017/hash/51e6d6e679953c6311757004d8cbbba9-Abstract.html",
          "authors": "Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman and Hugo Larochelle",
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          "year": "2017",
          "pub": "NIPS'17",
          "model": "NLBA",
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          "paper": "A Meta-Learning Perspective on Cold-Start Recommendations for Items",
          "paper_link": "https://proceedings.neurips.cc/paper/2017/hash/51e6d6e679953c6311757004d8cbbba9-Abstract.html",
          "authors": "Manasi Vartak, Arvind Thiagarajan, Conrado Miranda, Jeshua Bratman and Hugo Larochelle",
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          "repo_link": "https://github.com/nuster1128/RecBole-MetaRec"
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          "category": "Meta recommendation",
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          "year": "2019",
          "pub": "SIGIR'19",
          "model": "MetaEmb",
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          "paper": "Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings",
          "paper_link": "https://doi.org/10.1145/3331184.3331268",
          "authors": "Feiyang Pan, Shuokai Li, Xiang Ao, Pingzhong Tang and Qing He",
          "ref_code": "https://github.com/Feiyang/MetaEmbedding",
          "repository": "RecBole-MetaRec",
          "repo_link": "https://github.com/nuster1128/RecBole-MetaRec"
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          "year": "2021",
          "pub": "SIGIR'21",
          "model": "MWUF",
          "model_link": "https://github.com/nuster1128/RecBole-MetaRec/blob/master/recbole_metarec/model/MWUF",
          "paper": "Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks",
          "paper_link": "https://doi.org/10.1145/3404835.3462843",
          "authors": "Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang, Kaikai Ge, Ying Sun, Xu Zhang, Leyu Lin and Juan Cao",
          "ref_code": "",
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          "repo_link": "https://github.com/nuster1128/RecBole-MetaRec"
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          "category": "Debiased recommendation",
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          "year": "2009",
          "pub": "Computer'09",
          "model": "MF",
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          "paper": "Matrix Factorization Techniques for Recommender Systems",
          "paper_link": "https://ieeexplore.ieee.org/abstract/document/5197422",
          "authors": "Yehuda Koren, Robert Bell and Chris Volinsky",
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          "repo_link": "https://github.com/JingsenZhang/Recbole-Debias"
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          "pub": "ICML'16",
          "model": "MF-IPS",
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          "paper": "Recommendations as Treatments: Debiasing Learning and Evaluation",
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          "authors": "Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak and Thorsten Joachims",
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          "pub": "SIGIR'21",
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          "paper": "Causal Intervention for Leveraging Popularity Bias in Recommendation",
          "paper_link": "https://doi.org/10.1145/3404835.3462875",
          "authors": "Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling and Yongdong Zhang",
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          "pub": "SIGKDD'21",
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          "paper": "Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System",
          "paper_link": "https://doi.org/10.1145/3447548.3467289",
          "authors": "Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi and Xiangnan He",
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          "repository": "RecBole-Debias",
          "repo_link": "https://github.com/JingsenZhang/Recbole-Debias"
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          "category": "Debiased recommendation",
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          "year": "2021",
          "pub": "WWW'21",
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          "paper": "Disentangling User Interest and Conformity for Recommendation with Causal Embedding",
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          "authors": "Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Yong Li and Depeng Jin",
          "ref_code": "https://github.com/tsinghua-fib-lab/DICE",
          "repository": "RecBole-Debias",
          "repo_link": "https://github.com/JingsenZhang/Recbole-Debias"
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          "category": "Debiased recommendation",
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          "year": "2018",
          "pub": "RecSys'18",
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          "paper": "Causal Embeddings for Recommendation",
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          "authors": "Stephen Bonner and Flavian Vasile",
          "ref_code": "",
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          "repo_link": "https://github.com/JingsenZhang/Recbole-Debias"
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          "pub": "WSDM'20",
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          "paper": "Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback",
          "paper_link": "https://doi.org/10.1145/3336191.3371783",
          "authors": "Yuta Saito, Suguru Yaginuma, Yuta Nishino, Hayato Sakata and Kazuhide Nakata",
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          "pub": "NIPS'17",
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          "paper": "Beyond Parity: Fairness Objectives for Collaborative Filtering",
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          "authors": "Sirui Yao and Bert Huang",
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          "repo_link": "https://github.com/TangJiakai/RecBole-FairRec"
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          "year": "2021",
          "pub": "SIGIR'21",
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          "model_link": "https://github.com/TangJiakai/RecBole-FairRec/blob/master/recbole/model/fair_recommender/pfcn_mlp.py",
          "paper": "Towards Personalized Fairness based on Causal Notion",
          "paper_link": "https://doi.org/10.1145/3404835.3462966",
          "authors": "Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge and Yongfeng Zhang",
          "ref_code": "https://github.com/yunqi-li/Personalized-Counterfactual-Fairness-in-Recommendation",
          "repository": "RecBole-FairRec",
          "repo_link": "https://github.com/TangJiakai/RecBole-FairRec"
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          "category": "Fairness-aware recommendation",
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          "year": "2021",
          "pub": "WWW'21",
          "model": "FairGo",
          "model_link": "https://github.com/TangJiakai/RecBole-FairRec/blob/master/recbole/model/fair_recommender/fairgo_pmf.py",
          "paper": "Learning Fair Representations for Recommendation: A Graph-based Perspective",
          "paper_link": "https://doi.org/10.1145/3442381.3450015",
          "authors": "Le Wu, Lei Chen, Pengyang Shao, Richang Hong, Xiting Wang and Meng Wang",
          "ref_code": "https://github.com/newlei/FairGo",
          "repository": "RecBole-FairRec",
          "repo_link": "https://github.com/TangJiakai/RecBole-FairRec"
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          "category": "Cross-domain recommendation",
          "cate_link": "https://github.com/RUCAIBox/RecBole2.0#recbole-cdr",
          "year": "2008",
          "pub": "SIGKDD'08",
          "model": "CMF",
          "model_link": "https://github.com/RUCAIBox/RecBole-CDR/blob/main/recbole_cdr/model/cross_domain_recommender/cmf.py",
          "paper": "Relational Learning via Collective Matrix Factorization",
          "paper_link": "https://doi.org/10.1145/1401890.1401969",
          "authors": "Ajit P. Singh and Geoffrey J. Gordon",
          "ref_code": "",
          "repository": "RecBole-CDR",
          "repo_link": "https://github.com/RUCAIBox/RecBole-CDR"
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          "category": "Cross-domain recommendation",
          "cate_link": "https://github.com/RUCAIBox/RecBole2.0#recbole-cdr",
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          "authors": "Taeyong Kong, Taeri Kim, insung Jeon, Jeongwhan Choi, Yeon-Chang Lee, Noseong Park and Sang-Wook Kim",
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          "authors": "Hanxiao Liu, Zihang Dai, David So and Quoc V Le",
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          "repo_link": "https://github.com/RUCAIBox/RecBole-TRM"
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          "paper": "CORE: Simple and Effective Session-based Recommendation within Consistent Representation Space",
          "paper_link": "https://arxiv.org/abs/2204.11067",
          "authors": "Yupeng Hou, Binbin Hu, Zhiqiang Zhang and Wayne Xin Zhao",
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          "repo_link": "https://github.com/RUCAIBox/RecBole-TRM"
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          "pub": "EMNLP/IJCNLP'19",
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          "paper": "Neural News Recommendation with Multi-Head Self-Attention",
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          "authors": "Chuhan Wu, Fangzhao Wu, Suyu Ge, Tao Qi, Yongfeng Huang and Xing Xie",
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          "paper": "Neural News Recommendation with Attentive Multi-View Learning",
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          "authors": "Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang and Xing Xie",
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          "paper": "BPR: Bayesian Personalized Ranking from Implicit Feedback",
          "paper_link": "https://arxiv.org/abs/1205.2618",
          "authors": "Steffen Rendle, Christoph Freudenthaler, Zeno Gantner and Lars Schmidt-Thieme",
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          "repository": "RecBole-PJF",
          "repo_link": "https://github.com/RUCAIBox/RecBole-PJF"
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          "category": "Person-job Fit",
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          "pub": "WWW'17",
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          "paper": "Neural Collaborative Filtering",
          "paper_link": "https://doi.org/10.1145/3038912.3052569",
          "authors": "Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu and Tat-Seng Chua",
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          "repository": "RecBole-PJF",
          "repo_link": "https://github.com/RUCAIBox/RecBole-PJF"
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          "category": "Person-job Fit",
          "cate_link": "https://github.com/RUCAIBox/RecBole2.0#recbole-pjf",
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          "pub": "SIGIR'20",
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          "paper": "LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation",
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          "authors": "Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, YongDong Zhang and Meng Wang",
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          "repository": "RecBole-PJF",
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          "category": "Person-job Fit",
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          "pub": "RecSys'19",
          "model": "LFRR",
          "model_link": "https://github.com/RUCAIBox/RecBole-PJF/blob/main/recbole_pjf/model/lfrr.py",
          "paper": "Latent Factor Models and Aggregation Operators for Collaborative Filtering in Reciprocal Recommender systems",
          "paper_link": "https://doi.org/10.1145/3298689.3347026",
          "authors": "James Neve and Ivan Palomares",
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          "category": "Person-job Fit",
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          "pub": "TMIS'18",
          "model": "PJFNN",
          "model_link": "https://github.com/RUCAIBox/RecBole-PJF/blob/main/recbole_pjf/model/pjfnn.py",
          "paper": "Person-Job fit: Adapting the Right Talent for the Right Job with Joint Representation Learning",
          "paper_link": "https://doi.org/10.1145/3234465",
          "authors": "Chen Zhu, Hengshu Zhu, Hui Xiong, Chao Ma, Fang Xie, Pengliang Ding and Pan Li",
          "ref_code": "",
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          "category": "Person-job Fit",
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          "pub": "SIGIR'18",
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          "paper": "Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach",
          "paper_link": "https://doi.org/10.1145/3209978.3210025",
          "authors": "Chuan Qin, Hengshu Zhu, Tong Xu, Chen Zhu, Liang Jiang, Enhong Chen and Hui Xiong",
          "ref_code": "",
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          "repo_link": "https://github.com/RUCAIBox/RecBole-PJF"
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          "category": "Person-job Fit",
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          "pub": "SIGIR'18",
          "model": "APJFNN",
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          "paper": "Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach",
          "paper_link": "https://doi.org/10.1145/3209978.3210025",
          "authors": "Chuan Qin, Hengshu Zhu, Tong Xu, Chen Zhu, Liang Jiang, Enhong Chen and Hui Xiong",
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          "repo_link": "https://github.com/RUCAIBox/RecBole-PJF"
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          "model": "BERT",
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          "category": "Person-job Fit",
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          "pub": "CIKM'19",
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          "paper": "Towards Effective and Interpretable Person-Job Fitting",
          "paper_link": "https://doi.org/10.1145/3357384.3357949",
          "authors": "Ran Le, Wenpeng Hu, Yang Song, Tao Zhang, Dongyan Zhao and Rui Yan",
          "ref_code": "",
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          "repo_link": "https://github.com/RUCAIBox/RecBole-PJF"
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          "category": "Person-job Fit",
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          "pub": "CIKM'20",
          "model": "PJFFF",
          "model_link": "https://github.com/RUCAIBox/RecBole-PJF/blob/main/recbole_pjf/model/pjfff.py",
          "paper": "Learning Effective Representations for Person-Job Fit by Feature Fusion",
          "paper_link": "https://doi.org/10.1145/3340531.3412717",
          "authors": "Junshu Jiang, Songyun Ye, Wei Wang, Jingran Xu and Xiaosheng Luo",
          "ref_code": "",
          "repository": "RecBole-PJF",
          "repo_link": "https://github.com/RUCAIBox/RecBole-PJF"
      },
      {
          "category": "Person-job Fit",
          "cate_link": "https://github.com/RUCAIBox/RecBole2.0#recbole-pjf",
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          "pub": "DASFAA'22",
          "model": "SHPJF",
          "model_link": "https://github.com/RUCAIBox/RecBole-PJF/blob/main/recbole_pjf/model/shpjf.py",
          "paper": "Leveraging Search History for Improving Person-Job Fit",
          "paper_link": "https://link.springer.com/chapter/10.1007/978-3-031-00123-9_3",
          "authors": "Yupeng Hou, Xingyu Pan, Wayne Xin Zhao, Shuqing Bian, Yang Song, Tao Zhang and Ji-Rong Wen",
          "ref_code": "",
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        "paper": "LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation",
        "paper_link": "https://doi.org/10.1145/3397271.3401063",
        "authors": "Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, YongDong Zhang and Meng Wang",
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        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
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        "pub": "MDPI'18",
        "model": "CFKG",
        "model_link": "/docs/user_guide/model/knowledge/cfkg.html",
        "paper": "Learning heterogeneous knowledge base embeddings for explainable recommendation",
        "paper_link": "https://doi.org/10.3390/a11090137",
        "authors": "Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang",
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        "pub": "SIGKDD'16",
        "model": "CKE",
        "model_link": "/docs/user_guide/model/knowledge/cke.html",
        "paper": "Collaborative Knowledge Base Embedding for Recommender Systems",
        "paper_link": "https://doi.org/10.1145/2939672.2939673",
        "authors": "Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, Wei-Ying Ma",
        "ref_code": "",
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        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
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        "pub": "SIGKDD'19",
        "model": "KGAT",
        "model_link": "/docs/user_guide/model/knowledge/kgat.html",
        "paper": "KGAT: Knowledge Graph Attention Network for Recommendation",
        "paper_link": "https://doi.org/10.1145/3292500.3330989",
        "authors": "Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang ",
        "ref_code": "https://github.com/xiangwang1223/knowledge_graph_attention_network",
        "repository": "RecBole",
        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
        "year": "2019",
        "pub": "WWW'19",
        "model": "KGCN",
        "model_link": "/docs/user_guide/model/knowledge/kgcn.html",
        "paper": "Knowledge graph convolution networks for recommender systems",
        "paper_link": "https://doi.org/10.1145/3308558.3313417",
        "authors": "Hongwei Wang, Miao Zhao, Xing Xie, Wenjie Li, Minyi Guo",
        "ref_code": "https://github.com/hwwang55/KGCN",
        "repository": "RecBole",
        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
        "year": "2019",
        "pub": "SIGKDD'19",
        "model": "KGNN-LS",
        "model_link": "/docs/user_guide/model/knowledge/kgnnls.html",
        "paper": "Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems",
        "paper_link": "https://doi.org/10.48550/arXiv.1905.04413",
        "authors": "Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, Zhongyuan Wang",
        "ref_code": "https://github.com/hwwang55/KGNN-LS",
        "repository": "RecBole",
        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
        "year": "2019",
        "pub": "WWW'19",
        "model": "KTUP",
        "model_link": "/docs/user_guide/model/knowledge/ktup.html",
        "paper": "Unifying Knowledge Graph Learning and Recommendation:Towards a Better Understanding of User Preferences",
        "paper_link": "https://doi.org/10.1145/3308558.3313705",
        "authors": "Yixin Cao, Xiang Wang, Xiangnan He, Zikun hu, Tat-Seng Chua",
        "ref_code": "https://github.com/TaoMiner/joint-kg-recommender",
        "repository": "RecBole",
        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
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        "pub": "WWW'19",
        "model": "MKR",
        "model_link": "/docs/user_guide/model/knowledge/mkr.html",
        "paper": "Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation",
        "paper_link": "https://doi.org/10.48550/arXiv.1901.08907",
        "authors": "Hongwei Wang, Fuzheng Zhang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo",
        "ref_code": "https://github.com/hsientzucheng/MKR.PyTorch",
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        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
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        "pub": "CIKM'18",
        "model": "RippleNet",
        "model_link": "/docs/user_guide/model/knowledge/ripplenet.html",
        "paper": "Collaborative Knowledge Base Embedding for Recommender Systems",
        "paper_link": "https://dl.acm.org/doi/10.1145/3269206.3271739",
        "authors": "Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo",
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        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Knowledge-aware Recommendation",
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        "pub": "WWW'21",
        "model": "KGIN",
        "model_link": "/docs/user_guide/model/knowledge/kgin.html",
        "paper": "Learning Intents behind Interactions with Knowledge Graph for Recommendation",
        "paper_link": "https://dl.acm.org/doi/10.1145/3442381.3450133",
        "authors": "Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua",
        "ref_code": "",
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        "paper": "Collaborative Knowledge Base Embedding for Recommender Systems",
        "paper_link": "https://dl.acm.org/doi/10.1145/3477495.3532025",
        "authors": "Ding Zou, Wei Wei, Xian-Ling Mao, Ziyang Wang, Minghui Qiu, Feida Zhu, Xin Cao",
        "ref_code": "",
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        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "pub": "SIGIR'23",
        "model": "EulerNet",
        "model_link": "/docs/user_guide/model/context/eulernet.html",
        "paper": "EulerNet: Adaptive Feature Interaction Learning via Euler's Formula for CTR Prediction",
        "paper_link": "https://dl.acm.org/doi/10.1145/3539618.3591681",
        "authors": "Zhen Tian, Ting Bai, Wayne Xin Zhao, Ji-Rong Wen, Zhao Cao",
        "ref_code": "https://github.com/chenyuwuxin/EulerNet",
        "repository": "RecBole",
        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "Sequential Recommendation",
        "cate_link":  "/docs/user_guide/model_intro.html#sequential-recommendation",
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        "pub": "SIGIR'23",
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        "paper": "FEARec: Frequency Enhanced Hybrid Attention Network for Sequential Recommendation",
        "paper_link": "https://dl.acm.org/doi/10.1145/3539618.3591689",
        "authors": "Xinyu Du, Huanhuan Yuan, Pengpeng Zhao, Jianfeng Qu, Fuzhen Zhuang, Guanfeng Liu, Victor S. Sheng",
        "ref_code": "https://github.com/sudaada/FEARec",
        "repository": "RecBole",
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        "category": "General Recommendation",
        "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
        "year": "2023",
        "pub": "SIGIR'23",
        "model": "DiffRec",
        "model_link": "/docs/user_guide/model/general/diffrec.html",
        "paper": "Diffusion Recommender Model",
        "paper_link": "https://dl.acm.org/doi/10.1145/3539618.3591663",
        "authors": "Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua",
        "ref_code": "https://github.com/YiyanXu/DiffRec",
        "repository": "RecBole",
        "repo_link": "https://github.com/RUCAIBox/RecBole"
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        "category": "General Recommendation",
        "cate_link": "/docs/user_guide/model_intro.html#general-recommendation",
        "year": "2023",
        "pub": "SIGIR'23",
        "model": "LDiffRec",
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        "paper": "Diffusion Recommender Model",
        "paper_link": "https://dl.acm.org/doi/10.1145/3539618.3591663",
        "authors": "Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua",
        "ref_code": "https://github.com/YiyanXu/DiffRec",
        "repository": "RecBole",
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}