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RecSys 2021: Amsterdam, The Netherlands
- Humberto Jesús Corona Pampín, Martha A. Larson, Martijn C. Willemsen, Joseph A. Konstan, Julian J. McAuley, Jean Garcia-Gathright, Bouke Huurnink, Even Oldridge:
RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021 - 1 October 2021. ACM 2021, ISBN 978-1-4503-8458-2
Echo Chambers and Filter Bubbles
- Matús Tomlein, Branislav Pecher, Jakub Simko
, Ivan Srba
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes. 1-11 - Tim Donkers, Jürgen Ziegler:
The Dual Echo Chamber: Modeling Social Media Polarization for Interventional Recommending. 12-22 - Antonela Tommasel, Juan Manuel Rodriguez
I Want to Break Free! Recommending Friends from Outside the Echo Chamber. 23-33
Theory and Practice
- Harald Steck, Dawen Liang:
Negative Interactions for Improved Collaborative Filtering: Don't go Deeper, go Higher. 34-43 - Zhenrui Yue, Zhankui He, Huimin Zeng, Julian J. McAuley
Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction. 44-54 - Florian Wilhelm:
Matrix Factorization for Collaborative Filtering Is Just Solving an Adjoint Latent Dirichlet Allocation Model After All. 55-62 - Olivier Jeunen, Bart Goethals
Pessimistic Reward Models for Off-Policy Learning in Recommendation. 63-74
Metrics and Evaluation
- Javier Parapar, Filip Radlinski:
Towards Unified Metrics for Accuracy and Diversity for Recommender Systems. 75-84 - Minmin Chen, Yuyan Wang, Can Xu, Ya Le, Mohit Sharma, Lee Richardson, Su-Lin Wu, Ed H. Chi:
Values of User Exploration in Recommender Systems. 85-95 - Masahiro Sato:
Online Evaluation Methods for the Causal Effect of Recommendations. 96-101 - James McInerney, Ehtsham Elahi, Justin Basilico, Yves Raimond, Tony Jebara:
Accordion: A Trainable Simulator forLong-Term Interactive Systems. 102-113 - Yuta Saito, Takuma Udagawa, Haruka Kiyohara, Kazuki Mogi, Yusuke Narita, Kei Tateno:
Evaluating the Robustness of Off-Policy Evaluation. 114-123
Users in Focus
- Alain Starke
"Serving Each User": Supporting Different Eating Goals Through a Multi-List Recommender Interface. 124-132 - Ningxia Wang
User Bias in Beyond-Accuracy Measurement of Recommendation Algorithms. 133-142
Language and Knowledge
- Gabriel de Souza Pereira Moreira, Sara Rabhi, Jeongmin Lee, Ronay Ak, Even Oldridge:
Transformers4Rec: Bridging the Gap between NLP and Sequential / Session-Based Recommendation. 143-153 - Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara
Sparse Feature Factorization for Recommender Systems with Knowledge Graphs. 154-165 - Aravind Sankar, Junting Wang, Adit Krishnan, Hari Sundaram:
ProtoCF: Prototypical Collaborative Filtering for Few-shot Recommendation. 166-175 - Aghiles Salah, Thanh-Binh Tran, Hady W. Lauw
Towards Source-Aligned Variational Models for Cross-Domain Recommendation. 176-186 - Marco Polignano, Cataldo Musto, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro:
Together is Better: Hybrid Recommendations Combining Graph Embeddings and Contextualized Word Representations. 187-198 - Gaël Poux-Médard
Information Interactions in Outcome Prediction: Quantification and Interpretation using Stochastic Block Models. 199-208
Interactive Recommendation
- Diego Antognini, Boi Faltings:
Fast Multi-Step Critiquing for VAE-based Recommender Systems. 209-219 - Ali Montazeralghaem, James Allan, Philip S. Thomas:
Large-scale Interactive Conversational Recommendation System using Actor-Critic Framework. 220-229 - Yu Liang
The role of preference consistency, defaults and musical expertise in users' exploration behavior in a genre exploration recommender. 230-240 - Yaxiong Wu, Craig Macdonald, Iadh Ounis:
Partially Observable Reinforcement Learning for Dialog-based Interactive Recommendation. 241-251
Scalable Performance
- Longqi Yang, Tobias Schnabel, Paul N. Bennett, Susan T. Dumais:
Local Factor Models for Large-Scale Inductive Recommendation. 252-262 - Keshav Balasubramanian, Abdulla Alshabanah, Joshua D. Choe, Murali Annavaram:
cDLRM: Look Ahead Caching for Scalable Training of Recommendation Models. 263-272 - Daichi Amagata, Takahiro Hara:
Reverse Maximum Inner Product Search: How to efficiently find users who would like to buy my item? 273-281
Algorithmic Advances
- Wenzhuo Song
Next-item Recommendations in Short Sessions. 282-291 - Rodrigo Alves
Burst-induced Multi-Armed Bandit for Learning Recommendation. 292-301 - Viet-Anh Tran, Guillaume Salha-Galvan, Romain Hennequin, Manuel Moussallam:
Hierarchical Latent Relation Modeling for Collaborative Metric Learning. 302-309 - Olivier Jeunen, Bart Goethals
Top-K Contextual Bandits with Equity of Exposure. 310-320
Privacy, Fairness, Bias
- Khalil Damak, Sami Khenissi, Olfa Nasraoui
Debiased Explainable Pairwise Ranking from Implicit Feedback. 321-331 - Alon Ben Horin, Tamir Tassa:
Privacy Preserving Collaborative Filtering by Distributed Mediation. 332-341 - Lorenzo Minto, Moritz Haller, Benjamin Livshits, Hamed Haddadi:
Stronger Privacy for Federated Collaborative Filtering With Implicit Feedback. 342-350 - Dugang Liu, Pengxiang Cheng, Hong Zhu, Zhenhua Dong, Xiuqiang He, Weike Pan, Zhong Ming:
Mitigating Confounding Bias in Recommendation via Information Bottleneck. 351-360
Applications-Driven Advances
- Jyun-Yu Jiang, Chia-Jung Lee, Longqi Yang, Bahareh Sarrafzadeh, Brent J. Hecht, Jaime Teevan:
Learning to Represent Human Motives for Goal-directed Web Browsing. 361-371 - Yusuke Narita, Shota Yasui, Kohei Yata:
Debiased Off-Policy Evaluation for Recommendation Systems. 372-379 - Quentin Villermet, Jérémie Poiroux, Manuel Moussallam, Thomas Louail
Follow the guides: disentangling human and algorithmic curation in online music consumption. 380-389 - Jérémie Rappaz, Julian J. McAuley, Karl Aberer:
Recommendation on Live-Streaming Platforms: Dynamic Availability and Repeat Consumption. 390-399
Practical Issues
- Zhi Bian, Shaojun Zhou, Hao Fu, Qihong Yang, Zhenqi Sun, Junjie Tang, Guiquan Liu, Kaikui Liu, Xiaolong Li:
Denoising User-aware Memory Network for Recommendation. 400-410 - Danni Peng
Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems. 411-421 - Ramin Raziperchikolaei, Guannan Liang, Young-joo Chung:
Shared Neural Item Representations for Completely Cold Start Problem. 422-431 - Farwa K. Khan, Adrian Flanagan, Kuan Eeik Tan, Zareen Alamgir
A Payload Optimization Method for Federated Recommender Systems. 432-442
Real-World Concerns
- Guillaume Salha-Galvan, Romain Hennequin, Benjamin Chapus, Viet-Anh Tran, Michalis Vazirgiannis:
Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders. 443-452 - Huiyuan Chen, Yusan Lin, Fei Wang, Hao Yang:
Tops, Bottoms, and Shoes: Building Capsule Wardrobes via Cross-Attention Tensor Network. 453-462 - Ambareesh Revanur, Vijay Kumar, Deepthi Sharma:
Semi-Supervised Visual Representation Learning for Fashion Compatibility. 463-472 - Xin Zhou, Yang Li:
Large-Scale Modeling of Mobile User Click Behaviors Using Deep Learning. 473-483 - Yikun Xian, Tong Zhao, Jin Li, Jim Chan, Andrey Kan, Jun Ma
EX3: Explainable Attribute-aware Item-set Recommendations. 484-494 - Chieh Lo, Hongliang Yu, Xin Yin, Krutika Shetty, Changchen He, Kathy Hu, Justin M. Platz, Adam Ilardi, Sriganesh Madhvanath:
Page-level Optimization of e-Commerce Item Recommendations. 495-504
Reproducibility Papers
- Alexander Dallmann, Daniel Zoller, Andreas Hotho:
A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models. 505-514 - Ahtsham Manzoor
Generation-based vs. Retrieval-based Conversational Recommendation: A User-Centric Comparison. 515-520 - Vito Walter Anelli, Alejandro Bellogín
Reenvisioning the comparison between Neural Collaborative Filtering and Matrix Factorization. 521-529
Industry Papers
- Steven Essinger, Dave Huber, Daniel Tang:
AIR: Personalized Product Recommender System for Nike's Digital Transformation. 530-532 - Yuxi Zhang, Kexin Xie:
Boosting Local Recommendations With Partially Trained Global Model. 533-535 - Jakub Zavrel, Artem Grotov, Jonathan Mitnik:
Building a Platform for Ensemble-based Personalized Research Literature Recommendations for AI and Data Science at Zeta Alpha. 536-537 - Christina Boididou, Di Sheng, Felix J. Mercer Moss, Alessandro Piscopo:
Building Public Service Recommenders: Logbook of a Journey. 538-540 - Andreas Grün, Xenija Neufeld:
Challenges Experienced in Public Service Media Recommendation Systems. 541-544 - Niels Bogaards, Frederique Schut:
Content-based book recommendations: Personalised and explainable recommendations without the cold-start problem. 545-547 - Anna Gogleva, Eliseo Papa, Erik Jansson, Greet De Baets:
Drug Discovery as a Recommendation Problem: Challenges and Complexities in Biological Decisions. 548-550 - Minmin Chen:
Exploration in Recommender Systems. 551-553 - Daniel James Kershaw, Rob Koeling, Stephan Bourgeois, Antonio Trenta, Harriet J. Muncey
Fairness in Reviewer Recommendations at Elsevier. 554-555 - Simen Eide, David S. Leslie, Arnoldo Frigessi, Joakim Rishaug, Helge Jenssen, Sofie Verrewaere:
FINN.no Slates Dataset: A new Sequential Dataset Logging Interactions, all Viewed Items and Click Responses/No-Click for Recommender Systems Research. 556-558 - Hitesh Khandelwal, Viet Ha-Thuc, Avishek Dutta, Yining Lu, Nan Du
Jointly Optimize Capacity, Latency and Engagement in Large-scale Recommendation Systems. 559-561 - François Mairesse, Zhonghao Luo, Tao Ye:
Learning a Voice-based Conversational Recommender using Offline Policy Optimization. 562-564 - Dor Lavi:
Learning to Match Job Candidates Using Multilingual Bi-Encoder BERT. 565-566 - Chin Lin Wong, Diego Marinho de Oliveira, Farhad Zafari, Fernando Mourão, Rafael Colares, Sabir Ribas:
Offline Evaluation Standards for Recommender Systems. 567-568 - Alex Egg:
Online Learning for Recommendations at Grubhub. 569-571 - Nick Landia:
Personalised Outfit Recommendations: Use Cases, Challenges and Opportunities. 572-574 - Shayak Banerjee, Arnab Bhadury, Nilothpal Talukder, Santosh Thammana:
Personalizing Peloton: Combining Rankers and Filters To Balance Engagement and Business Goals. 575-576 - Sudarshan Dnyaneshwar Lamkhede, Christoph Kofler:
Recommendations and Results Organization in Netflix Search. 577-579 - Mateo Gutierrez Granada, Daan Odijk:
Recommendations at Videoland. 580-582 - Ioannis Kangas, Maud Schwoerer, Lucas J. Bernardi:
Recommender Systems for Personalized User Experience: Lessons learned at Booking.com. 583-586 - Carlos Vaquero-Patricio, Nikki Van Ommeren, Santiago Gil-Begue:
Recommenders in Banking: An End-to-end Personalization Pipeline within ING. 587-589 - Mohammad Saberian, Justin Basilico:
RecSysOps: Best Practices for Operating a Large-Scale Recommender System. 590-591 - Maurits van der Goes
Scaling Enterprise Recommender Systems for Decentralization. 592-594 - Jan Hartman, Davorin Kopic:
Scaling TensorFlow to 300 million predictions per second. 595-597 - Jacopo Tagliabue:
You Do Not Need a Bigger Boat: Recommendations at Reasonable Scale in a (Mostly) Serverless and Open Stack. 598-600
Late-breaking Results
- Oleg Lesota, Alessandro B. Melchiorre
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected? 601-606 - Sinan Seymen, Himan Abdollahpouri, Edward C. Malthouse:
A Constrained Optimization Approach for Calibrated Recommendations. 607-612 - Conor O'Brien, Kin Sum Liu, James Neufeld, Rafael Barreto, Jonathan J. Hunt:
An Analysis Of Entire Space Multi-Task Models For Post-Click Conversion Prediction. 613-619 - Andre Paulino de Lima
An Interpretable Recommendation Model for Gerontological Care. 620-626 - Pedro Ramaciotti Morales
Auditing the Effect of Social Network Recommendations on Polarization in Geometrical Ideological Spaces. 627-632 - Sanidhya Singal
Automatic Collection Creation and Recommendation. 633-638 - Lawrence Spear, Ashlee Milton, Garrett Allen
Baby Shark to Barracuda: Analyzing Children's Music Listening Behavior. 639-644 - Thi Ngoc Trang Tran, Viet Man Le, Muesluem Atas, Alexander Felfernig, Martin Stettinger, Andrei Popescu:
Do Users Appreciate Explanations of Recommendations? An Analysis in the Movie Domain. 645-650 - Rui Ye, Yuqing Hou, Te Lei, Yunxing Zhang, Qing Zhang, Jiale Guo, Huaiwen Wu, Hengliang Luo:
Dynamic Graph Construction for Improving Diversity of Recommendation. 651-655 - Cesare Bernardis, Paolo Cremonesi:
Eigenvalue Perturbation for Item-based Recommender Systems. 656-660 - Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
Estimating and Penalizing Preference Shift in Recommender Systems. 661-667 - Zhaohao Lin
FR-FMSS: Federated Recommendation via Fake Marks and Secret Sharing. 668-673 - Seungjae Jung, Young-Jin Park, Jisu Jeong, Kyung-Min Kim, Hiun Kim, Minkyu Kim, Hanock Kwak:
Global-Local Item Embedding for Temporal Set Prediction. 674-679 - Saikishore Kalloori, Severin Klingler:
Horizontal Cross-Silo Federated Recommender Systems. 680-684 - Yuhi Kawakami, Mahito Sugiyama:
Investigating Overparameterization for Non-Negative Matrix Factorization in Collaborative Filtering. 685-690 - Maurizio Ferrari Dacrema
Optimizing the Selection of Recommendation Carousels with Quantum Computing. 691-696 - Giovanni Gabbolini, Derek Bridge:
Play It Again, Sam! Recommending Familiar Music in Fresh Ways. 697-701 - Markus Reiter-Haas
Predicting Music Relistening Behavior Using the ACT-R Framework. 702-707 - Yan-Martin Tamm, Rinchin Damdinov, Alexey Vasilev
Quality Metrics in Recommender Systems: Do We Calculate Metrics Consistently? 708-713 - Stefanos Antaris, Dimitrios Rafailidis:
Sequence Adaptation via Reinforcement Learning in Recommender Systems. 714-718 - Michael Pulis, Josef Bajada
Siamese Neural Networks for Content-based Cold-Start Music Recommendation. 719-723 - Ivica Kostric, Krisztian Balog, Filip Radlinski:
Soliciting User Preferences in Conversational Recommender Systems via Usage-related Questions. 724-729 - Vito Walter Anelli, Tommaso Di Noia, Felice Antonio Merra:
The Idiosyncratic Effects of Adversarial Training on Bias in Personalized Recommendation Learning. 730-735 - Zinan Lin, Dugang Liu, Weike Pan, Zhong Ming:
Transfer Learning in Collaborative Recommendation for Bias Reduction. 736-740
Demonstrations
- Claudio Di Sipio
A Low-Code Tool Supporting the Development of Recommender Systems. 741-744 - Behnam Rahdari, Peter Brusilovsky, Alireza Javadian Sabet
Connecting Students with Research Advisors Through User-Controlled Recommendation. 745-748 - Michael Färber
DataHunter: A System for Finding Datasets Based on Scientific Problem Descriptions. 749-752 - Vuong Thanh Tung
EntityBot: Supporting Everyday Digital Tasks with Entity Recommendations. 753-756 - Royi Ronen, Hilik Berezin, Rotem Preizler, Gopal Kasturi, A. J. Ezzour, Sayalee Bhanavase, Edan Hauon, Oron Nir:
Generic Automated Lead Ranking in Dynamics CRM. 757-759 - Diana Andreea Petrescu, Diego Antognini, Boi Faltings:
Multi-Step Critiquing User Interface for Recommender Systems. 760-763 - Ernesto Diaz-Aviles, Claudia Orellana-Rodriguez, Igor Brigadir
NU: BRIEF - A Privacy-aware Newsletter Personalization Engine for Publishers. 764-767 - Vito Walter Anelli, Alejandro Bellogín
V-Elliot: Design, Evaluate and Tune Visual Recommender Systems. 768-771
Workshops and Challenge
- Özlem Özgöbek
9th International Workshop on News Recommendation and Analytics. 772-774 - Himan Abdollahpouri, Toine Bogers, Bamshad Mobasher
ComplexRec 2021: Fifth Workshop on Recommendation in Complex Environments. 775-777 - Michael D. Ekstrand, Pierre-Nicolas Schwab, Toshihiro Kamishima, Nasim Sonboli:
FAccTRec 2021: The 4th Workshop on Responsible Recommendation. 778-779 - Thibaut Thonet, Stéphane Clinchant, Carlos Lassance, Elvin Isufi, Jiaqi Ma, Yutong Xie, Jean-Michel Renders, Michael M. Bronstein:
GReS: Workshop on Graph Neural Networks for Recommendation and Search. 780-782 - Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Elisabeth Lex, Pasquale Lops, Giovanni Semeraro, Martijn C. Willemsen
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS'21). 783-786 - Himan Abdollahpouri, Mehdi Elahi, Masoud Mansoury, Shaghayegh Sahebi, Zahra Nazari, Allison Chaney, Babak Loni:
MORS 2021: 1st Workshop on Multi-Objective Recommender Systems. 787-788 - Antonela Tommasel, Daniela Godoy, Arkaitz Zubiaga:
OHARS: Second Workshop on Online Misinformation- and Harm-Aware Recommender Systems. 789-791 - João Vinagre
ORSUM 2021 - 4th Workshop on Online Recommender Systems and User Modeling. 792-793 - Eva Zangerle, Christine Bauer
Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES). 794-795 - Ching-Wei Chen, Rosie Jones, Zahra Nazari, Longqi Yang, Maria Eskevich, Gareth James Francis Jones, Sergio Oramas:
PodRecs 2021: 2nd Workshop on Podcast Recommendations. 796-798 - Toine Bogers, David Graus
RecSys in HR: Workshop on Recommender Systems for Human Resources. 799-802 - Michael D. Ekstrand, Allison Chaney, Pablo Castells
SimuRec: Workshop on Synthetic Data and Simulation Methods for Recommender Systems Research. 803-805 - Vito Walter Anelli, Pierpaolo Basile
Third Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). 806-809 - Shatha Jaradat, Nima Dokoohaki
Workshop on Recommender Systems in Fashion and Retail. 810-812 - Gediminas Adomavicius, Konstantin Bauman
Workshop on Context-Aware Recommender Systems (CARS) 2021. 813-814 - Julia Neidhardt, Wolfgang Wörndl, Tsvi Kuflik, Markus Zanker:
Workshop on Recommenders in Tourism (RecTour). 815-816 - Mohammad Aliannejadi
XMRec: Workshop on Cross-Market Recommendation. 817-818 - Vito Walter Anelli, Saikishore Kalloori, Bruce Ferwerda, Luca Belli, Alykhan Tejani, Frank Portman, Alexandre Lung-Yut-Fong, Ben Chamberlain, Yuanpu Xie, Jonathan Hunt, Michael M. Bronstein, Wenzhe Shi:
RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter's Home Timeline. 819-824
Tutorials
- Jiawei Chen, Xiang Wang, Fuli Feng, Xiangnan He:
Bias Issues and Solutions in Recommender System: Tutorial on the RecSys 2021. 825-827 - Yuta Saito, Thorsten Joachims:
Counterfactual Learning and Evaluation for Recommender Systems: Foundations, Implementations, and Recent Advances. 828-830 - Gabriel de Souza Pereira Moreira, Sara Rabhi, Ronay Ak, Benedikt Schifferer:
End-to-End Session-Based Recommendation on GPU. 831-833 - Quoc-Tuan Truong, Aghiles Salah, Hady W. Lauw
Multi-Modal Recommender Systems: Hands-On Exploration. 834-837 - Vito Walter Anelli, Luca Belli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara
Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to Applications. 838-841 - Wenqiang Lei, Chongming Gao, Maarten de Rijke:
RecSys 2021 Tutorial on Conversational Recommendation: Formulation, Methods, and Evaluation. 842-844
Doctoral Symposium
- Andrés Segura-Tinoco
Argument-based generation and explanation of recommendations. 845-850 - Bolanle Olufisayo Dahunsi
An Ontology-based Knowledgebase for User Profile and Garment Features in Apparel Recommender Systems. 851-854 - Saumya Bhadani:
Biases in Recommendation System. 855-859 - Simone Borg Bruun:
Learning Dynamic Insurance Recommendations from Users' Click Sessions. 860-863 - Pan Li:
Leveraging Multi-Faceted User Preferences for Improving Click-Through Rate Predictions. 864-868 - Muhammad Ali:
Measuring and Mitigating Bias and Harm in Personalized Advertising. 869-872 - Mete Sertkan:
Modeling Users and Items for Recommenders: There Is More than Semantics. 873-877 - Vojtech Vancura
Neural Basket Embedding for Sequential Recommendation. 878-883
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