recsys 2021 论文列表
RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021 - 1 October 2021.
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Neural Basket Embedding for Sequential Recommendation.
Modeling Users and Items for Recommenders: There Is More than Semantics.
Measuring and Mitigating Bias and Harm in Personalized Advertising.
Leveraging Multi-Faceted User Preferences for Improving Click-Through Rate Predictions.
Learning Dynamic Insurance Recommendations from Users' Click Sessions.
Biases in Recommendation System.
An Ontology-based Knowledgebase for User Profile and Garment Features in Apparel Recommender Systems.
Argument-based generation and explanation of recommendations.
RecSys 2021 Tutorial on Conversational Recommendation: Formulation, Methods, and Evaluation.
Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to Applications.
Multi-Modal Recommender Systems: Hands-On Exploration.
End-to-End Session-Based Recommendation on GPU.
Counterfactual Learning and Evaluation for Recommender Systems: Foundations, Implementations, and Recent Advances.
Bias Issues and Solutions in Recommender System: Tutorial on the RecSys 2021.
RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter's Home Timeline.
XMRec: Workshop on Cross-Market Recommendation.
Workshop on Recommenders in Tourism (RecTour).
Workshop on Context-Aware Recommender Systems (CARS) 2021.
Workshop on Recommender Systems in Fashion and Retail.
Third Knowledge-aware and Conversational Recommender Systems Workshop (KaRS).
SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research.
RecSys in HR: Workshop on Recommender Systems for Human Resources.
PodRecs 2021: 2nd Workshop on Podcast Recommendations.
Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES).
ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling.
OHARS: Second Workshop on Online Misinformation- and Harm-Aware Recommender Systems.
MORS 2021: 1st Workshop on Multi-Objective Recommender Systems.
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS'21).
GReS: Workshop on Graph Neural Networks for Recommendation and Search.
FAccTRec 2021: The 4th Workshop on Responsible Recommendation.
ComplexRec 2021: Fifth Workshop on Recommendation in Complex Environments.
9th International Workshop on News Recommendation and Analytics.
V-Elliot: Design, Evaluate and Tune Visual Recommender Systems.
NU: BRIEF - A Privacy-aware Newsletter Personalization Engine for Publishers.
Multi-Step Critiquing User Interface for Recommender Systems.
Generic Automated Lead Ranking in Dynamics CRM.
EntityBot: Supporting Everyday Digital Tasks with Entity Recommendations.
DataHunter: A System for Finding Datasets Based on Scientific Problem Descriptions.
Connecting Students with Research Advisors Through User-Controlled Recommendation.
A Low-Code Tool Supporting the Development of Recommender Systems.
Transfer Learning in Collaborative Recommendation for Bias Reduction.
The Idiosyncratic Effects of Adversarial Training on Bias in Personalized Recommendation Learning.
Soliciting User Preferences in Conversational Recommender Systems via Usage-related Questions.
Siamese Neural Networks for Content-based Cold-Start Music Recommendation.
Sequence Adaptation via Reinforcement Learning in Recommender Systems.
Quality Metrics in Recommender Systems: Do We Calculate Metrics Consistently?
Predicting Music Relistening Behavior Using the ACT-R Framework.
Play It Again, Sam! Recommending Familiar Music in Fresh Ways.
Optimizing the Selection of Recommendation Carousels with Quantum Computing.
Investigating Overparameterization for Non-Negative Matrix Factorization in Collaborative Filtering.
Horizontal Cross-Silo Federated Recommender Systems.
Global-Local Item Embedding for Temporal Set Prediction.
FR-FMSS: Federated Recommendation via Fake Marks and Secret Sharing.
Estimating and Penalizing Preference Shift in Recommender Systems.
Eigenvalue Perturbation for Item-based Recommender Systems.
Dynamic Graph Construction for Improving Diversity of Recommendation.
Do Users Appreciate Explanations of Recommendations? An Analysis in the Movie Domain.
Baby Shark to Barracuda: Analyzing Children's Music Listening Behavior.
Automatic Collection Creation and Recommendation.
Auditing the Effect of Social Network Recommendations on Polarization in Geometrical Ideological Spaces.
An Interpretable Recommendation Model for Gerontological Care.
An Analysis Of Entire Space Multi-Task Models For Post-Click Conversion Prediction.
A Constrained Optimization Approach for Calibrated Recommendations.
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
You Do Not Need a Bigger Boat: Recommendations at Reasonable Scale in a (Mostly) Serverless and Open Stack.
Scaling TensorFlow to 300 million predictions per second.
Scaling Enterprise Recommender Systems for Decentralization.
RecSysOps: Best Practices for Operating a Large-Scale Recommender System.
Recommenders in Banking: An End-to-end Personalization Pipeline within ING.
Recommender Systems for Personalized User Experience: Lessons learned at Booking.com.
Recommendations at Videoland.
Recommendations and Results Organization in Netflix Search.
Personalizing Peloton: Combining Rankers and Filters To Balance Engagement and Business Goals.
Personalised Outfit Recommendations: Use Cases, Challenges and Opportunities.
Online Learning for Recommendations at Grubhub.
Offline Evaluation Standards for Recommender Systems.
Learning to Match Job Candidates Using Multilingual Bi-Encoder BERT.
Learning a Voice-based Conversational Recommender using Offline Policy Optimization.
Jointly Optimize Capacity, Latency and Engagement in Large-scale Recommendation Systems.
FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, all Viewed Items and Click Responses/No-Click for Recommender Systems Research.
Fairness in Reviewer Recommendations at Elsevier.
Exploration in Recommender Systems.
Drug Discovery as a Recommendation Problem: Challenges and Complexities in Biological Decisions.
Content-based book recommendations: Personalised and explainable recommendations without the cold-start problem.
Challenges Experienced in Public Service Media Recommendation Systems.
Building Public Service Recommenders: Logbook of a Journey.
Building a Platform for Ensemble-based Personalized Research Literature Recommendations for AI and Data Science at Zeta Alpha.
Boosting Local Recommendations With Partially Trained Global Model.
AIR: Personalized Product Recommender System for Nike's Digital Transformation.
Reenvisioning the comparison between Neural Collaborative Filtering and Matrix Factorization.
Generation-based vs. Retrieval-based Conversational Recommendation: A User-Centric Comparison.
A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models.
Page-level Optimization of e-Commerce Item Recommendations.
EX3: Explainable Attribute-aware Item-set Recommendations.
Large-Scale Modeling of Mobile User Click Behaviors Using Deep Learning.
Semi-Supervised Visual Representation Learning for Fashion Compatibility.
Tops, Bottoms, and Shoes: Building Capsule Wardrobes via Cross-Attention Tensor Network.
Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders.
A Payload Optimization Method for Federated Recommender Systems.
Shared Neural Item Representations for Completely Cold Start Problem.
Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems.
Denoising User-aware Memory Network for Recommendation.
Recommendation on Live-Streaming Platforms: Dynamic Availability and Repeat Consumption.
Follow the guides: disentangling human and algorithmic curation in online music consumption.
Debiased Off-Policy Evaluation for Recommendation Systems.
Learning to Represent Human Motives for Goal-directed Web Browsing.
Mitigating Confounding Bias in Recommendation via Information Bottleneck.
Stronger Privacy for Federated Collaborative Filtering With Implicit Feedback.
Privacy Preserving Collaborative Filtering by Distributed Mediation.
Debiased Explainable Pairwise Ranking from Implicit Feedback.
Top-K Contextual Bandits with Equity of Exposure.
Hierarchical Latent Relation Modeling for Collaborative Metric Learning.
Burst-induced Multi-Armed Bandit for Learning Recommendation.
Next-item Recommendations in Short Sessions.
Reverse Maximum Inner Product Search: How to efficiently find users who would like to buy my item?
cDLRM: Look Ahead Caching for Scalable Training of Recommendation Models.
Local Factor Models for Large-Scale Inductive Recommendation.
Partially Observable Reinforcement Learning for Dialog-based Interactive Recommendation.
The role of preference consistency, defaults and musical expertise in users' exploration behavior in a genre exploration recommender.
Large-scale Interactive Conversational Recommendation System using Actor-Critic Framework.
Fast Multi-Step Critiquing for VAE-based Recommender Systems.
Information Interactions in Outcome Prediction: Quantification and Interpretation using Stochastic Block Models.
Together is Better: Hybrid Recommendations Combining Graph Embeddings and Contextualized Word Representations.
Towards Source-Aligned Variational Models for Cross-Domain Recommendation.
ProtoCF: Prototypical Collaborative Filtering for Few-shot Recommendation.
Sparse Feature Factorization for Recommender Systems with Knowledge Graphs.
Transformers4Rec: Bridging the Gap between NLP and Sequential / Session-Based Recommendation.
User Bias in Beyond-Accuracy Measurement of Recommendation Algorithms.
"Serving Each User": Supporting Different Eating Goals Through a Multi-List Recommender Interface.
Evaluating the Robustness of Off-Policy Evaluation.
Accordion: A Trainable Simulator forLong-Term Interactive Systems.
Online Evaluation Methods for the Causal Effect of Recommendations.
Values of User Exploration in Recommender Systems.
Towards Unified Metrics for Accuracy and Diversity for Recommender Systems.
Pessimistic Reward Models for Off-Policy Learning in Recommendation.
Matrix Factorization for Collaborative Filtering Is Just Solving an Adjoint Latent Dirichlet Allocation Model After All.
Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction.
Negative Interactions for Improved Collaborative Filtering: Don't go Deeper, go Higher.
I Want to Break Free! Recommending Friends from Outside the Echo Chamber.
The Dual Echo Chamber: Modeling Social Media Polarization for Interventional Recommending.
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes.
