推荐系统2019-2021顶尖会议论文聚焦

https://download.csdn.net/download/qq_39693517/15732675

• recommendation & deep learning

  

  – AAAI_2020_A Knowledge-Aware Attentional Reasoning Network for Recommendation.pdf
  – AAAI_2020_An Attentional Recurrent Neural Network for Personalized Next Location Recommendation.pdf
  – AAAI_2020_Diversified Interactive Recommendation with Implicit Feedback.pdf
  – AAAI_2020_Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation.pdf
  – AAAI_2020_Leveraging Title-Abstract Attentive Semantics for Paper Recommendation.pdf
  – AAAI_2020_Memory Augmented Graph Neural Networks for Sequential Recommendation.pdf
  – AAAI_2020_PEIA Personality and Emotion Integrated Attentive Model for Music Recommendation on Social Media Platforms.pdf
  – AAAI_2020_Where to Go Next Modeling Long-and Short#U00ac┸Term User Preferences for Point-#U00acof┸Interest Recommendation.pdf
  – AAAI_2021_A Hybrid Bandit Framework for Diversified Recommendation.pdf
  – AAAI_2021_DEAR Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems.pdf
  – AAAI_2021_Graph Heterogeneous Multi-Relational Recommendation.pdf
  – AAAI_2021_Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation.pdf
  – AAAI_2021_Knowledge-aware Coupled Graph Neural Network for Social Recommendation.pdf
  – AAAI_2021_Non-invasive Self-attention for Side Information Fusion in Sequential Recommendation.pdf
  – AAAI_2021_U-BERT Pre-training User Representations for Improved Recommendation.pdf
  – AAAI_2021_Who You Would Like to Share With A Study of Share Recommendation in Social E-commerce.pdf
  – ACL_2020_Dynamic Online Conversation Recommendation.pdf
  – ACL_2020_Fine-grained Interest Matching for Neural News Recommendation.pdf
  – ACL_2020_Graph Neural News Recommendation with Unsupervised Preference Disentanglement.pdf
  – IJCAI_2019_Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommendation.pdf
  – IJCAI_2019_BPAM：Recommendation Based on BP Neural Network with Attention Mechainsm.pdf
  – IJCAI_2019_CFM：Convolutional Factorization Machines for Context-Aware Recommendation.pdf
  – IJCAI_2019_Collaborative Metric Learning with Memory Network for Multi Relational Recommender Systems.pdf
  – IJCAI_2019_Matching User with Item Set：Collaborative Bundle Recommendation with Attention Network.pdf
  – IJCAI_2019_PD-GAN：Adversarial Learning for Personalized Diversity-Promoting Recommendation.pdf
  – IJCAI_2020_An Interactive Multi-Task Learning Framework for Next POI Recommendation with Uncertain Check-ins.pdf
  – IJCAI_2020_Collaborative Self-Attention Network for Session-based Recommendation.pdf
  – IJCAI_2020_Deep Feedback Network for Recommendation.pdf
  – IJCAI_2020_Discovering Subsequence Patterns for Next POI Recommendation.pdf
  – IJCAI_2020_Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability.pdf
  – IJCAI_2020_Intent Preference Decoupling for User Representation on Online Recommender System.pdf
  – IJCAI_2020_Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation.pdf
  – IJCAI_2020_Learning Personalized Itemset Mapping for Cross-Domain Recommendation.pdf
  – IJCAI_2020_Neural Tensor Model for Learning Multi-Aspect Factors in Recommender Systems.pdf
  – IJCAI_2020_User Modeling with Click Preference and Reading Satisfaction for News Recommendation.pdf
  – KDD_2020_An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph.pdf
  – KDD_2020_Category-Specific CNN for Visual-aware CTR Prediction at JD.com.pdf
  – KDD_2020_Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems.pdf
  – KDD_2020_Controllable Multi-Interest Framework for Recommendation.pdf
  – KDD_2020_Disentangled Self-Supervision in Sequential Recommenders.pdf
  – KDD_2020_Dual Channel Hypergraph Collaborative Filtering.pdf
  – KDD_2020_Embedding-based Retrieval in Facebook Search.pdf
  – KDD_2020_Geography-Aware Sequential Location Recommendation.pdf
  – KDD_2020_Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion.pdf
  – KDD_2020_Improving Recommendation Quality in Google Drive.pdf
  – KDD_2020_Interactive Path Reasoning on Graph for Conversational Recommendation.pdf
  – KDD_2020_Jointly Learning to Recommend and Advertise.pdf
  – KDD_2020_M2GRL- A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems.pdf
  – KDD_2020_Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation.pdf
  – KDD_2020_Privileged Features Distillation at Taobao Recommendations.pdf
  – Recsys_2020_Contextual and Sequential User Embeddings for Large-Scale Music Recommendation.pdf
  – Recsys_2020_FISSA_ Fusing Item Similarity Models with Self-Attention Networks for Sequential Recommendation.pdf
  – Recsys_2020_KRED_ Knowledge-Aware Document Representation for News Recommendations.pdf
  – Recsys_2020_Long-tail Session-based Recommendation.pdf
  – Recsys_2020_Neural Collaborative Filtering vs. Matrix Factorization Revisited.pdf
  – Recsys_2020_Progressive Layered Extraction (PLE)_ A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations.pdf
  – Recsys_2020_RecSeats_ A Hybrid Convolutional Neural Network Choice Model for Seat Recommendations at Reserved Seating Venues.pdf
  – Recsys_2020_SSE-PT_ Sequential Recommendation Via Personalized Transformer.pdf
  – Recsys_2020_TAFA_ Two-headed Attention Fused Autoencoder for Context-Aware Recommendations.pdf
  – SIGIR_2020_A General Network Compression Framework for Sequential Recommender Systems…pdf
  – SIGIR_2020_Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View.pdf
  – SIGIR_2020_Content-aware Neural Hashing for Cold-start Recommendation.pdf
  – SIGIR_2020_Distributed Equivalent Substitution Training for Large-Scale Recommender Systems.pdf
  – SIGIR_2020_GAG- Global Attributed Graph Neural Network for Streaming Session-based Recommendation.pdf
  – SIGIR_2020_GroupIM- A Mutual Information Maximization Framework for Neural Group Recommendation.pdf
  – SIGIR_2020_Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation.pdf
  – SIGIR_2020_Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning…pdf
  – SIGIR_2020_Joint Item Recommendation and Attribute Inference- An Adaptive Graph Convolutional Network Approach.pdf
  – SIGIR_2020_Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation.pdf
  – SIGIR_2020_MVIN- Learning Multiview Items for Recommendation.pdf
  – SIGIR_2020_Neural Interactive Collaborative Filtering.pdf
  – SIGIR_2020_Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation.pdf
  – SIGIR_2020_Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste.pdf
  – SIGIR_2020_Sequential Recommendation with Self-attentive Multi-adversarial Network.pdf
  – SIGIR_2020_Spatial Object Recommendation with Hints- When Spatial Granularity Matters.pdf
  – WWW_2020_A Category-Aware Deep Model for Successive POI Recommendation on Sparse Check-in Data.pdf
  – WWW_2020_A Contextualized Temporal Attention Mechanism for Sequential Recommendation.pdf
  – WWW_2020_Adversarial Multimodal Representation Learning forClick-Through Rate Prediction.pdf
  – WWW_2020_Attentive Sequential Models of Latent Intent for Next Item Recommendation.pdf
  – WWW_2020_Deep Global and Local Generative Model for Recommendation.pdf
  – WWW_2020_Directional and Explainable Serendipity Recommendation.pdf
  – WWW_2020_Efficient Non-Sampling Factorization Machines for Optimal Context-Aware Recommendation.pdf
  – WWW_2020_Future Data Helps Training-Modeling Future Contexts for Session-based Recommendation.pdf
  – WWW_2020_Graph Enhanced Representation Learningfor News Recommendation.pdf
  – WWW_2020_Intention Modeling from Ordered and Unordered Facets forSequential Recommendation.pdf
  – WWW_2020_Keywords Generation ImprovesE-Commerce Session-based Recommendation.pdf
  – WWW_2020_Learning to Hash with Graph Neural Networksfor Recommender Systems.pdf
  – WWW_2020_LightRec_ a Memory and Search-Efficient Recommender System.pdf
  – WWW_2020_Personalized Employee Training Course Recommendation with Career Development Awareness.pdf
  – WWW_2020_Recommending Themes for Ad Creative Design via Visual-Linguistic Representations.pdf

• recommendation & graph

  

  – AAAI_2020_Attention‐guide Walk Model in Heterogeneous Information Network for Multi-­style Recommendation…pdf
  – AAAI_2020_Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation.pdf
  – AAAI_2020_Knowledge-aware Coupled Graph Neural Network for Social Recommendation.pdf
  – AAAI_2020_Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation.pdf
  – AAAI_2020_Multi-Component Graph Convolutional Collaborative Filtering.pdf
  – AAAI_2021_Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation.pdf
  – CIKM_2020_CAFE Coarse-to-Fine Knowledge Graph Reasoning for E-Commerce Recommendation.pdf
  – CIKM_2020_DisenHAN Disentangled Heterogeneous Graph Attention Network for Recommendation.pdf
  – CIKM_2020_Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation.pdf
  – CIKM_2020_Multiplex Graph Neural Networks for Multi-behavior Recommendation.pdf
  – CIKM_2020_News Recommendation with Topic-Enriched Knowledge Graphs.pdf
  – CIKM_2020_Star Graph Neural Networks for Session-based Recommendation.pdf
  – CIKM_2020_TGCN Tag Graph Convolutional Network.pdf
  – IJCAI_2019_Graph Contextualized Self-Attention Network for Session-based Recommendation.pdf
  – IJCAI_2019_Graph Convolutional Networks on User Mobility Heterogeneous Graphs for Social Relationship Inference.pdf
  – IJCAI_2019_Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation…pdf
  – IJCAI_2019_STAR-GCN_ Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems.pdf
  – IJCAI_2020_A Graphical and Attentional Framework for Dual-Target Cross-Domain.pdf
  – IJCAI_2020_Contextualized Point-of-Interest Recommendation.pdf
  – SIGIR_2020_A Heterogeneous Graph Neural Model for Cold-Start Recommendation.pdf
  – SIGIR_2020_A Knowledge-Enhanced Recommendation Model.pdf
  – SIGIR_2020_ATBRG_ Adaptive Target-Behavior Relational Graph Network for Effective Recommendation.pdf
  – SIGIR_2020_Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View.pdf
  – SIGIR_2020_Bundle Recommendation with Graph Convolutional Networks.pdf
  – SIGIR_2020_Disentangled Graph Collaborative Filtering.pdf
  – SIGIR_2020_Enhancing Recommendation Diversity using Determinantal Point Processes on Knowledge Graphs.pdf
  – SIGIR_2020_Fairness-Aware Explainable Recommendation over Knowledge Graphs.pdf
  – SIGIR_2020_GAG_ Global Attributed Graph Neural Network for Streaming.pdf
  – SIGIR_2020_GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Identification.pdf
  – SIGIR_2020_Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation.pdf
  – SIGIR_2020_Hierarchical Fashion Graph Network for Personalized Outfit Recommendation.pdf
  – SIGIR_2020_Incorporating User Micro-behaviors and Item Knowledge.pdf
  – SIGIR_2020_Interactive Recommender System via Knowledge.pdf
  – SIGIR_2020_Joint Item Recommendation and Attribute Inference An Adaptive Graph Convolutional Network Approach…pdf
  – SIGIR_2020_Jointly Non-Sampling Learning for Knowledge Graph Enhanced.pdf
  – SIGIR_2020_Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation.pdf
  – SIGIR_2020_LightGCN Simplifying and Powering Graph Convolution Network for Recommendation.pdf
  – SIGIR_2020_Multi-behavior Recommendation with Graph Convolutional Networks.pdf
  – SIGIR_2020_Neighbor Interaction Aware Graph Convolution Networks for Recommendation.pdf
  – SIGIR_2020_Next-item Recommendation with Sequential Hypergraphs.pdf
  – SIGIR_2020_TAGNN_ Target Attentive Graph Neural Networks for Session-based Recommendation.pdf
  – WSDM_2021_Bipartite Graph Embedding via Mutual Information Maximization-WSDM.pdf
  – WSDM_2021_Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction-WSDM.pdf
  – WSDM_2021_Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation-WSDM.pdf
  – WSDM_2021_Temporal Meta-path Guided Explainable Recommendation-WSDM.pdf
  – WWW_2020_Graph Enhanced Representation Learning for News Recommendation.pdf
  – WWW_2020_Learning to Hash with Graph Neural Networks for Recommender Systems.pdf
  – WWW_2020_paper2repo GitHub Repository Recommendation for Academic.pdf
  – WWW_2020_Reinforced Negative Sampling over Knowledge Graph for.pdf
  – WWW_2020_Weakly Supervised Attention for Hashtag Recommendation using Graph Data.pdf

• recommendation & learning

  

  – AAAI_2019_Hierarchical Reinforcement Learning for Course Recommendation in MOOCs.pdf
  – AIED_2019_Adaptive Learning Material Recommendation in Online Language Education.pdf
  – AIED_2020_Book_ArtificialIntelligenceInEducat.pdf
  – CIKM_2019_Exploring Multi-Objective Exercise Recommendations.pdf
  – CIKM_2019_Learning to be Relevant Evolution of a Course Recommendation System.pdf
  – CSEDU_2020_Recommendation of Educational Content to Improve Student PerformanceAn Approach based on Learning Styles.pdf
  – EDM2019_Concept-Aware Deep Knowledge Tracing and Exercise.pdf
  – EDM2020_Course Recommendation for University Environments.pdf
  – EDM2020_Recommending Remedial Readings Using Student Knowledge State.pdf
  – Education and Information Technologies_2020_A systematic review_machine learning based recommendation systems for e-learning.pdf
  – Expert Systems with Applications_2020_Learning path personalization and recommendation methods.pdf
  – Information Science_2020_Knowledge modeling via contextualized representations for.pdf
  – KBS_2020_A learning path recommendation model based on a multidimensional.pdf
  – KBS_2020_Exercise recommendation based on knowledge concept prediction.pdf
  – KDD2019_Exploiting Cognitive Structure for Adaptive Learning.pdf
  – L@S_2020_Interpretable Personalized Knowledge Tracing and Next.pdf
  – LAK19_Goal-based Course Recommendation.pdf
  – LAK_2020_Designing for Serendipity in a University Course.pdf
  – SIGIR_2020_Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View.pdf
  – WWW_2020_Personalized Employee Training Course Recommendation with.pdf

• recommendation & session-based

  

  – AAAI_2019_RepeatNet A Repeat Aware Neural Recommendation Machine for session-based recommendation.pdf
  – AAAI_2019_Session-based Recommendation with Graph Neural Networks.pdf
  – AAAI_2021_Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation.pdf
  – AAAI_2021_Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation.pdf
  – An Intent-guided Collaborative Machine for Session-based Recommendation.pdf
  – CIKM_2017_Neural Attentive Session-based Recommendation.pdf
  – CIKM_2018_Recurrent neural networks with top-k gains for session-based recommendations.pdf
  – CIKM_2019_A Dynamic Co-attention Network for Session-based Recommendation.pdf
  – CIKM_2019_Rethinking the Item Order in Session-based Recommendation with Graph Neural Network.pdf
  – CIKM_2020_Star Graph Neural Networks for Session-based Recommendation.pdf
  – ICLR_2016_Session-based recommendations with recurrent neural networks.pdf
  – IJCAI_2019_Graph Contextual Self-Attention Network for Session-based Recommendation.pdf
  – IJCAI_2020_Collaborative Self-Attention Network for Session-based Recommendation.pdf
  – KDD_2018_STAMP Short-Term Attention Memory Priority Model for Session-based Recommendation.pdf
  – KDD_2020_Handling Information Loss of Graph Neural Networks for Session-based Recommendation.pdf
  – Recsys_2017_3D Convolutional Networks for Session-based Recommendation with Content features.pdf
  – Recsys_2020_Exploring Longitudinal Effects of Session-based Recommendations.pdf
  – Recsys_2020_Long-tail Session-based Recommendation.pdf
  – SIGIR_2019_A Collaborative Session-based Recommendation Approach with Parallel Memory Modules.pdf
  – SIGIR_2020_Global Context Enhanced Graph Neural Networks for Session-based Recommendation.pdf
  – SIGIR_2020_Rethinking Item Importance in Session-based Recommendation.pdf
  – SIGIR_2020_Session-based Recommendation with Hierarchical Leaping Networks.pdf
  – WWW_2020_Keywords Generation Improves E-Commerce Session-based Recommendation.pdf

• recommendation & user modeling

  

  – AAAI_2020_Intention Nets Psychology-inspired User Choice Behavior Modeling.pdf
  – CIKM_2020_Prospective Modeling of Users for Online Display Advertising.pdf
  – CIKM_2020_Search-based User Interest Modeling with Lifelong Sequential.pdf
  – HCI_2020_Modeling User Information Needs to Enable Successful Human Machine Teams Designing Transparency in Autonomous Systems.pdf
  – IJCAI_2020_A Survey on Representation Learning for User Modeling.pdf
  – IJCAI_2020_User Modeling with Click Preference and Reading Satisfaction.pdf
  – KDD_2019_Log2Intent Towards Interpretable User Modeling via RecurrentSemantics Memor y Unit.pdf
  – KDD_2019_Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction.pdf
  – KDD_2019_Practice on Long Sequential User Behavior Modeling for.pdf
  – KDD_2020_Calendar Graph Neural Networks for Modeling Time Structures.pdf
  – KDD_2020_Incremental Mobile User Profiling Reinforcement Learning.pdf
  – KDD_2020_Learning Transferrable Parameters for Long-tailed SequentialUser Behavior Modeling.pdf
  – SIGIR_2019_Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction.pdf
  – UMAP_2019_Modeling Behavior Patterns with an Unfamiliar Voice User Interface.pdf
  – UMUAI_2020_Better targeting of consumers Modeling multifactorial gender and biological sex from Instagram posts.pdf
  – UMUAI_2020_Modeling real-time data and contextual information from workouts in eCoaching platforms to predict users’ sharing behavior on Facebook.pdf
  – UMUAI_2020_Modeling the behavior of persons with mild cognitive impairment or Alzheimer’s for intelligent environment simulation.pdf
  – UMUAI_2020_Myrror a platform for holistic user modeling.pdf
  – WSDM_2019_Domain Switch-Aware Holistic Recurrent Neural Network.pdf
  – WSDM_2019_User Behavior Modeling for Web Image Search.pdf
  – WWW_2019_Modeling the Factors of User Success in Online Debate.pdf
  – WWW_2019_TiSSA A Time Slice Self-Attention Approach for Modeling Sequential User Behaviors.pdf
  – WWW_2020_Modeling Users Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection.pdf

标签：based,Graph,2019,SIGIR,2020,2021,顶尖,Recommendation,pdf
来源： https://blog.csdn.net/qq_39693517/article/details/114648038