This project maintains a reading list for Data Denoising Metrics in Recommender System.
- AutoField: Automating Feature Selection in Deep Recommender Systems. WWW 2022
- Bayesian feature interaction selection for factorization machines Aitif Intell 2022
- Autofis: Automatic feature interaction selection in factorization models for click-through rate prediction . KDD 2020
- Bayesian Personalized feature interaction selection for factorization machines. SIGIR 2019
- FiBiNET: combining feature importance and bilinear feature interaction for click-through rate prediction. RecSys 2019
- FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine. ICDM 2019
- Autocross: Automatic feature crossing for tabular data in real-world application. KDD 2019
- Autoint: Automatic feature interaction learning via self- attentive neural network. CIKM 2019
- Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks. IJCAI 2017
- Feature Selection for FM-based Context-Aware. ISM 2017
- Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks. IJCAI 2017
- Selecting Content-Based Features for Collaborative Filtering Recommenders. RecSys 2013
- Xbox Movies Recommendations: Variational Bayes Matrix Factorization with Embedded Feature Selection. RecSys 2013
- Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering. SIGIR 2022
- Self-Guided Learning to Denoise for Robust Recommendation. SIGIR 2022
- Denoising Time Cycle Modeling for Recommendation. SIGIR 2022
- Denoising-Guided Deep Reinforcement Learning For Social Recommendation. ICASSP 2022
- Denoising-Oriented Deep Hierarchical Reinforcement Learning for Next-Basket Recommendation. ICASSP 2022
- Denoising Self-Attentive Sequential Recommendation. RecSys 2022
- LCD: Adaptive Label Correction for Denoising Music Recommendation. CIKM 2022
- Hierarchical Item Inconsistency Signal Learning for Sequence Denoising in Sequential Recommendation. CIKM 2022
- Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback. NAACL-HLT 2022
- Denoising User-aware Memory Network for Recommendation. RecSys 2021
- The World is Binary Contrastive Learning for Denoising Next Basket Recommendation. SIGIR 2021
- Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation. CIKM 2021
- Denoising Implicit Feedback for Recommendation. WSDM 2021
- Pattern-enhanced Contrastive Policy Learning Network for Sequential Recommendation. IJCAI 2021
- Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction. CIKM 2020
- Deep Interest Network for Click-Through Rate Prediction. KDD 2018
- Explainable Session-based Recommendation with Meta-path Guided Instances and Self-Attention Mechanism. SIGIR 2022
- A Knowledge-Aware Attentional Reasoning Network for Recommendation. AAAI 2020
- Explainable Reasoning over Knowledge Graphs for Recommendation. AAAI 2019
- Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation. WWW 2019
- Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation. KDD 2019
- Unified Collaborative Filtering over Graph Embeddings. SIGIR 2019
- Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. SIGIR 2019
- Leveraging Meta-path based Context for Top-N Recommendation with A Neural Co-Attention Model. KDD 2018
- RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems. CIKM 2018
- Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks. SIGIR 2018
- DKN: Deep Knowledge-Aware Network for News Recommendation. WWW 2018
- Learning over knowledge-base embeddings for recommendation. CoRR 2018
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Multi-Agent RL-based Information Selection Model for Sequential Recommendation. SIGIR 2022
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Review-Aware Neural Recommendation with Cross-Modality Mutual Attention. CIKM 2021
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Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback. ACM Multimedia 2020
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User Diverse Preference Modeling by Multimodal Attentive Metric Learning. ACM Multimedia 2019
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MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video. ACM Multimedia 2019
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Visually Explainable Recommendation. SIGIR 2019
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Interpretable Convolutional Neural Networks with Dual Local and Global Aention for Review Rating Prediction. RecSys 2017
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