Neural Collaborative Filtering vs. Matrix Factorization Revisited |
Steffen Rendle, Walid Krichene, Li Zhang, John R. Anderson |
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code |
142 |
Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations |
Hongyan Tang, Junning Liu, Ming Zhao, Xudong Gong |
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code |
92 |
SSE-PT: Sequential Recommendation Via Personalized Transformer |
Liwei Wu, Shuqing Li, ChoJui Hsieh, James Sharpnack |
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code |
44 |
The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation |
Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher |
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code |
40 |
Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison |
Zhu Sun, Di Yu, Hui Fang, Jie Yang, Xinghua Qu, Jie Zhang, Cong Geng |
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code |
40 |
Contextual and Sequential User Embeddings for Large-Scale Music Recommendation |
Casper Hansen, Christian Hansen, Lucas Maystre, Rishabh Mehrotra, Brian Brost, Federico Tomasi, Mounia Lalmas |
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code |
32 |
Long-tail Session-based Recommendation |
Siyi Liu, Yujia Zheng |
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code |
28 |
Causal Inference for Recommender Systems |
Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei |
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code |
27 |
KRED: Knowledge-Aware Document Representation for News Recommendations |
Danyang Liu, Jianxun Lian, Shiyin Wang, Ying Qiao, JiunHung Chen, Guangzhong Sun, Xing Xie |
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code |
26 |
Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems |
Jin Huang, Harrie Oosterhuis, Maarten de Rijke, Herke van Hoof |
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code |
25 |
Bias in Search and Recommender Systems |
Ricardo BaezaYates |
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code |
22 |
Doubly Robust Estimator for Ranking Metrics with Post-Click Conversions |
Yuta Saito |
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code |
20 |
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models |
Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis |
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code |
20 |
Context-aware Graph Embedding for Session-based News Recommendation |
HengShiou Sheu, Sheng Li |
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code |
19 |
Ensuring Fairness in Group Recommendations by Rank-Sensitive Balancing of Relevance |
Mesut Kaya, Derek G. Bridge, Nava Tintarev |
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code |
18 |
FISSA: Fusing Item Similarity Models with Self-Attention Networks for Sequential Recommendation |
Jing Lin, Weike Pan, Zhong Ming |
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code |
18 |
MEANTIME: Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation |
Sung Min Cho, Eunhyeok Park, Sungjoo Yoo |
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code |
17 |
Personality Bias of Music Recommendation Algorithms |
Alessandro B. Melchiorre, Eva Zangerle, Markus Schedl |
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code |
15 |
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks |
Leyla Mirvakhabova, Evgeny Frolov, Valentin Khrulkov, Ivan V. Oseledets, Alexander Tuzhilin |
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code |
15 |
A Federated Recommender System for Online Services |
Ben Tan, Bo Liu, Vincent W. Zheng, Qiang Yang |
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code |
15 |
What does BERT know about books, movies and music? Probing BERT for Conversational Recommendation |
Gustavo Penha, Claudia Hauff |
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code |
14 |
ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation |
Fei Mi, Xiaoyu Lin, Boi Faltings |
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code |
14 |
Content-Collaborative Disentanglement Representation Learning for Enhanced Recommendation |
Yin Zhang, Ziwei Zhu, Yun He, James Caverlee |
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code |
13 |
Explainable Recommendations via Attentive Multi-Persona Collaborative Filtering |
Oren Barkan, Yonatan Fuchs, Avi Caciularu, Noam Koenigstein |
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code |
13 |
Unbiased Implicit Recommendation and Propensity Estimation via Combinational Joint Learning |
Ziwei Zhu, Yun He, Yin Zhang, James Caverlee |
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code |
12 |
Revisiting Adversarially Learned Injection Attacks Against Recommender Systems |
Jiaxi Tang, Hongyi Wen, Ke Wang |
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12 |
PURS: Personalized Unexpected Recommender System for Improving User Satisfaction |
Pan Li, Maofei Que, Zhichao Jiang, Yao Hu, Alexander Tuzhilin |
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code |
11 |
Unbiased Learning for the Causal Effect of Recommendation |
Masahiro Sato, Sho Takemori, Janmajay Singh, Tomoko Ohkuma |
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code |
11 |
Exploring Longitudinal Effects of Session-based Recommendations |
Andres Ferraro, Dietmar Jannach, Xavier Serra |
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code |
9 |
Deconstructing the Filter Bubble: User Decision-Making and Recommender Systems |
Guy Aridor, Duarte Gonçalves, Shan Sikdar |
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code |
9 |
Combining Rating and Review Data by Initializing Latent Factor Models with Topic Models for Top-N Recommendation |
Francisco J. Peña, Diarmuid O'ReillyMorgan, Elias Z. Tragos, Neil Hurley, Erika Duriakova, Barry Smyth, Aonghus Lawlor |
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9 |
Free Lunch! Retrospective Uplift Modeling for Dynamic Promotions Recommendation within ROI Constraints |
Dmitri Goldenberg, Javier Albert, Lucas Bernardi, Pablo Estevez |
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code |
9 |
Tuning Word2vec for Large Scale Recommendation Systems |
Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein |
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code |
9 |
Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity |
Chang Li, Haoyun Feng, Maarten de Rijke |
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code |
8 |
Counteracting Bias and Increasing Fairness in Search and Recommender Systems |
Ruoyuan Gao, Chirag Shah |
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code |
8 |
Exploring Clustering of Bandits for Online Recommendation System |
Liu Yang, Bo Liu, Leyu Lin, Feng Xia, Kai Chen, Qiang Yang |
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code |
8 |
From the lab to production: A case study of session-based recommendations in the home-improvement domain |
Pigi Kouki, Ilias Fountalis, Nikolaos Vasiloglou, Xiquan Cui, Edo Liberty, Khalifeh Al Jadda |
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code |
8 |
Unbiased Ad Click Prediction for Position-aware Advertising Systems |
BoWen Yuan, Yaxu Liu, JuiYang Hsia, Zhenhua Dong, ChihJen Lin |
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code |
8 |
Learning to Collaborate in Multi-Module Recommendation via Multi-Agent Reinforcement Learning without Communication |
Xu He, Bo An, Yanghua Li, Haikai Chen, Rundong Wang, Xinrun Wang, Runsheng Yu, Xin Li, Zhirong Wang |
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code |
8 |
TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations |
Jin Peng Zhou, Zhaoyue Cheng, Felipe Pérez, Maksims Volkovs |
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code |
8 |
Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG |
Martin Mladenov, ChihWei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov, Craig Boutilier |
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code |
8 |
Tutorial on Conversational Recommendation Systems |
Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang |
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code |
7 |
Carousel Personalization in Music Streaming Apps with Contextual Bandits |
Walid Bendada, Guillaume Salha, Théo Bontempelli |
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code |
7 |
Interpretable Contextual Team-aware Item Recommendation: Application in Multiplayer Online Battle Arena Games |
Andrés Villa, Vladimir Araujo, Francisca Cattan, Denis Parra |
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code |
7 |
Global and Local Differential Privacy for Collaborative Bandits |
Huazheng Wang, Qian Zhao, Qingyun Wu, Shubham Chopra, Abhinav Khaitan, Hongning Wang |
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code |
7 |
In-Store Augmented Reality-Enabled Product Comparison and Recommendation |
Jesús Omar Álvarez Márquez, Jürgen Ziegler |
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code |
7 |
Introduction to Bandits in Recommender Systems |
Andrea BarrazaUrbina, Dorota Glowacka |
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code |
7 |
A Ranking Optimization Approach to Latent Linear Critiquing for Conversational Recommender Systems |
Hanze Li, Scott Sanner, Kai Luo, Ga Wu |
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code |
6 |
Deep Bayesian Bandits: Exploring in Online Personalized Recommendations |
Dalin Guo, Sofia Ira Ktena, Pranay Kumar Myana, Ferenc Huszar, Wenzhe Shi, Alykhan Tejani, Michael Kneier, Sourav Das |
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code |
6 |
Theoretical Modeling of the Iterative Properties of User Discovery in a Collaborative Filtering Recommender System |
Sami Khenissi, Mariem Boujelbene, Olfa Nasraoui |
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code |
6 |
On Target Item Sampling in Offline Recommender System Evaluation |
Rocío Cañamares, Pablo Castells |
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code |
6 |
Recommending the Video to Watch Next: An Offline and Online Evaluation at YOUTV.de |
Panagiotis Symeonidis, Andrea Janes, Dmitry Chaltsev, Philip Giuliani, Daniel Morandini, Andreas Unterhuber, Ludovik Coba, Markus Zanker |
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code |
6 |
Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems |
Caojin Zhang, Yicun Liu, Yuanpu Xie, Sofia Ira Ktena, Alykhan Tejani, Akshay Gupta, Pranay Kumar Myana, Deepak Dilipkumar, Suvadip Paul, Ikuhiro Ihara, Prasang Upadhyaya, Ferenc Huszar, Wenzhe Shi |
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code |
6 |
Providing Explainable Race-Time Predictions and Training Plan Recommendations to Marathon Runners |
Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
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code |
6 |
Inferring the Causal Impact of New Track Releases on Music Recommendation Platforms through Counterfactual Predictions |
Rishabh Mehrotra, Prasanta Bhattacharya, Mounia Lalmas |
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code |
6 |
Deconfounding User Satisfaction Estimation from Response Rate Bias |
Konstantina Christakopoulou, Madeleine Traverse, Trevor Potter, Emma Marriott, Daniel Li, Chris Haulk, Ed H. Chi, Minmin Chen |
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code |
6 |
Offline Contextual Multi-armed Bandits for Mobile Health Interventions: A Case Study on Emotion Regulation |
Mawulolo K. Ameko, Miranda L. Beltzer, Lihua Cai, Mehdi Boukhechba, Bethany A. Teachman, Laura E. Barnes |
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code |
6 |
Making Neural Networks Interpretable with Attribution: Application to Implicit Signals Prediction |
Darius Afchar, Romain Hennequin |
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code |
6 |
Towards Safety and Sustainability: Designing Local Recommendations for Post-pandemic World |
Gourab K. Patro, Abhijnan Chakraborty, Ashmi Banerjee, Niloy Ganguly |
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code |
5 |
Explainable Recommendation for Repeat Consumption |
Kosetsu Tsukuda, Masataka Goto |
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code |
5 |
Reducing energy waste in households through real-time recommendations |
Janhavi Dahihande, Akshay Jaiswal, Akshay Anil Pagar, Ajinkya Thakare, Magdalini Eirinaki, Iraklis Varlamis |
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code |
5 |
Fairness-aware Recommendation with librec-auto |
Nasim Sonboli, Robin Burke, Zijun Liu, Masoud Mansoury |
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code |
5 |
ImRec: Learning Reciprocal Preferences Using Images |
James Neve, Ryan McConville |
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code |
5 |
Towards Multi-Language Recipe Personalisation and Recommendation |
Niall Twomey, Mikhail Fain, Andrey Ponikar, Nadine Sarraf |
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code |
4 |
Counterfactual learning for recommender system |
Zhenhua Dong, Hong Zhu, Pengxiang Cheng, Xinhua Feng, Guohao Cai, Xiuqiang He, Jun Xu, Jirong Wen |
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code |
4 |
BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems |
Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis, Siwei Liu, Yaxiong Wu, Xi Wang, Shangsong Liang, Yucheng Liang, Guangtao Zeng, Junhua Liang, Qiang Zhang |
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code |
4 |
PicTouRe - A Picture-Based Tourism Recommender |
Mete Sertkan, Julia Neidhardt, Hannes Werthner |
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code |
4 |
Closed-Form Models for Collaborative Filtering with Side-Information |
Olivier Jeunen, Jan Van Balen, Bart Goethals |
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code |
4 |
Evolutionary Approach in Recommendation Systems for Complex Structured Objects |
Bartolomé Ortiz Viso |
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code |
4 |
"Don't Judge a Book by its Cover": Exploring Book Traits Children Favor |
Ashlee Milton, Levesson Batista, Garrett Allen, Siqi Gao, YiuKai Ng, Maria Soledad Pera |
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code |
4 |
History-Augmented Collaborative Filtering for Financial Recommendations |
Baptiste Barreau, Laurent Carlier |
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code |
3 |
Fit to Run: Personalised Recommendations for Marathon Training |
Jakim Berndsen, Barry Smyth, Aonghus Lawlor |
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code |
3 |
Debiasing Item-to-Item Recommendations With Small Annotated Datasets |
Tobias Schnabel, Paul N. Bennett |
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code |
3 |
Contextual Meta-Bandit for Recommender Systems Selection |
Marlesson R. O. Santana, Luckeciano C. Melo, Fernando H. F. Camargo, Bruno Brandão, Anderson Soares, Renan M. Oliveira, Sandor Caetano |
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code |
3 |
RecSeats: A Hybrid Convolutional Neural Network Choice Model for Seat Recommendations at Reserved Seating Venues |
Théo Moins, Daniel Aloise, Simon J. Blanchard |
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code |
3 |
"Who doesn't like dinosaurs?" Finding and Eliciting Richer Preferences for Recommendation |
Tobias Schnabel, Gonzalo A. Ramos, Saleema Amershi |
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code |
3 |
Investigating Listeners' Responses to Divergent Recommendations |
Rishabh Mehrotra, Chirag Shah, Benjamin A. Carterette |
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code |
3 |
Adversarial Learning for Recommendation: Applications for Security and Generative Tasks - Concept to Code |
Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra |
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code |
3 |
ClusterExplorer: Enable User Control over Related Recommendations via Collaborative Filtering and Clustering |
Denis Kotkov, Qian Zhao, Kati Launis, Mats Neovius |
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code |
2 |
Contextual User Browsing Bandits for Large-Scale Online Mobile Recommendation |
Xu He, Bo An, Yanghua Li, Haikai Chen, Qingyu Guo, Xin Li, Zhirong Wang |
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code |
2 |
The Embeddings That Came in From the Cold: Improving Vectors for New and Rare Products with Content-Based Inference |
Jacopo Tagliabue, Bingqing Yu, Federico Bianchi |
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code |
2 |
MultiRec: A Multi-Relational Approach for Unique Item Recommendation in Auction Systems |
Ahmed Rashed, Shayan Jawed, Lars SchmidtThieme, Andre Hintsches |
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code |
2 |
Auto-Surprise: An Automated Recommender-System (AutoRecSys) Library with Tree of Parzens Estimator (TPE) Optimization |
Rohan Anand, Joeran Beel |
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code |
2 |
Online Recommender system for Accessible Tourism Destinations |
Luchiana Cezara Brodeala |
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code |
2 |
Building a reciprocal recommendation system at scale from scratch: Learnings from one of Japan's prominent dating applications |
R. Ramanathan, Nicolas K. Shinada, Sucheendra K. Palaniappan |
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code |
2 |
AutoRec: An Automated Recommender System |
TingHsiang Wang, Xia Hu, Haifeng Jin, Qingquan Song, Xiaotian Han, Zirui Liu |
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code |
2 |
Interfaces and Human Decision Making for Recommender Systems |
Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Giovanni Semeraro, Martijn C. Willemsen |
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code |
2 |
A College Major Recommendation System |
Samuel Alexander Stein, Gary M. Weiss, Yiwen Chen, Daniel D. Leeds |
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code |
2 |
DRecPy: A Python Framework for Developing Deep Learning-Based Recommenders |
Fábio Colaço, Márcia Barros, Francisco M. Couto |
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code |
2 |
Learning Representations of Hierarchical Slates in Collaborative Filtering |
Ehtsham Elahi, Ashok Chandrashekar |
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code |
2 |
Characterizing and Mitigating the Impact of Data Imbalance for Stakeholders in Recommender Systems |
Elizabeth Gómez |
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code |
2 |
Tutorial: Feature Engineering for Recommender Systems |
Benedikt Schifferer, Chris Deotte, Even Oldridge |
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code |
2 |
Efficiency-Effectiveness Trade-offs in Recommendation Systems |
Iulia Paun |
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code |
2 |
REVEAL 2020: Bandit and Reinforcement Learning from User Interactions |
Thorsten Joachims, Yves Raimond, Olivier Koch, Maria Dimakopoulou, Flavian Vasile, Adith Swaminathan |
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code |
2 |
Investigating the Impact of Audio States & Transitions for Track Sequencing in Music Streaming Sessions |
Aaron Ng, Rishabh Mehrotra |
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code |
2 |
4 Reasons Why Social Media Make Us Vulnerable to Manipulation |
Filippo Menczer |
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code |
2 |
Adaptive Pointwise-Pairwise Learning-to-Rank for Content-based Personalized Recommendation |
Yagmur Gizem Cinar, JeanMichel Renders |
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code |
1 |
Query as Context for Item-to-Item Recommendation |
Moumita Bhattacharya, Amey Barapatre |
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code |
1 |
Improving One-class Recommendation with Multi-tasking on Various Preference Intensities |
ChuJen Shao, HaoMing Fu, PuJen Cheng |
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code |
1 |
Exploiting Performance Estimates for Augmenting Recommendation Ensembles |
Gustavo Penha, Rodrygo L. T. Santos |
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code |
1 |
Recommendations as Graph Explorations |
Marialena Kyriakidi, Georgia Koutrika, Yannis E. Ioannidis |
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code |
1 |
Investigating Multimodal Features for Video Recommendations at Globoplay |
Felipe Ferreira, Daniele R. Souza, Igor Moura, Matheus Barbieri, Hélio Côrtes Vieira Lopes |
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code |
1 |
A Method to Anonymize Business Metrics to Publishing Implicit Feedback Datasets |
Yoshifumi Seki, Takanori Maehara |
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code |
1 |
A Human Perspective on Algorithmic Similarity |
Zachary A. Schendel, Faraz Farzin, Siddhi Sundar |
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code |
1 |
Developing Recommendation System to provide a Personalized Learning experience at Chegg |
Sanghamitra Deb |
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code |
0 |
Do Channels Matter? Illuminating Interpersonal Influence on Music Recommendations |
Hyun Jeong Kim, So Yeon Park, Minju Park, Kyogu Lee |
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code |
0 |
Conversational Agents for Recommender Systems |
Andrea Iovine |
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code |
0 |
"You Really Get Me": Conversational AI Agents That Can Truly Understand and Help Users |
Michelle X. Zhou |
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code |
0 |
Behavior-based Popularity Ranking on Amazon Video |
Lakshmi Ramachandran |
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code |
0 |
A Joint Dynamic Ranking System with DNN and Vector-based Clustering Bandit |
Yu Liu, Xiaoxiao Xu, Jincheng Wang, Yong Li, Changping Peng, Yongjun Bao, Weipeng P. Yan |
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code |
0 |
Exploratory Methods for Evaluating Recommender Systems |
Joey De Pauw |
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code |
0 |
Taking advantage of images and texts in recommender systems: semantics and explainability |
Pablo PérezNúñez |
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code |
0 |
Goal-driven Command Recommendations for Analysts |
Samarth Aggarwal, Rohin Garg, Abhilasha Sancheti, Bhanu Prakash Reddy Guda, Iftikhar Ahamath Burhanuddin |
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code |
0 |
Using conceptual incongruity as a basis for making recommendations |
Tushar Shandhilya, Nisheeth Srivastava |
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code |
0 |
Balancing Relevance and Discovery to Inspire Customers in the IKEA App |
Balázs Tóth, Sandhya Sachidanandan, Emil S. Jørgensen |
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code |
0 |
Recommender-Systems.com: A Central Platform for the Recommender-System Community |
Joeran Beel |
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code |
0 |
Recommending in changing times |
Shruti Kunde, Mayank Mishra, Amey Pandit, Rekha Singhal, Manoj Karunakaran Nambiar, Gautam Shroff, Shashank Gupta |
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code |
0 |
Smart Targeting: A Relevance-driven and Configurable Targeting Framework for Advertising System |
Yong Li, Zihao Zhao, Zhiwei Fang, Kui Ma, Yafei Yao, Changping Peng, Yongjun Bao, Weipeng Yan |
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code |
0 |
Bayesian Value Based Recommendation: A modelling based alternative to proxy and counterfactual policy based recommendation |
David Rohde, Flavian Vasile, Sergey Ivanov, Otmane Sakhi |
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code |
0 |
Developing Work in Confidence, Similarity Structure, and Modeling User Event Time |
Jacob Munson |
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code |
0 |
On the Heterogeneous Information Needs in the Job Domain: A Unified Platform for Student Career |
Markus ReiterHaas, David Wittenbrink, Emanuel Lacic |
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code |
0 |
VMI-PSL: Visual Model Inspector for Probabilistic Soft Logic |
Aaron Rodden, Tarun Salh, Eriq Augustine, Lise Getoor |
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code |
0 |