| Are we really making much progress? A worrying analysis of recent neural recommendation approaches |
Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach |
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code |
222 |
| Recommending what video to watch next: a multitask ranking system |
Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, Ed H. Chi |
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code |
116 |
| FiBiNET: combining feature importance and bilinear feature interaction for click-through rate prediction |
Tongwen Huang, Zhiqi Zhang, Junlin Zhang |
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code |
83 |
| Performance comparison of neural and non-neural approaches to session-based recommendation |
Malte Ludewig, Noemi Mauro, Sara Latifi, Dietmar Jannach |
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code |
53 |
| Personalized re-ranking for recommendation |
Changhua Pei, Yi Zhang, Yongfeng Zhang, Fei Sun, Xiao Lin, Hanxiao Sun, Jian Wu, Peng Jiang, Junfeng Ge, Wenwu Ou, Dan Pei |
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code |
50 |
| Sampling-bias-corrected neural modeling for large corpus item recommendations |
Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, Ed H. Chi |
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code |
48 |
| Deep social collaborative filtering |
Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li |
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code |
43 |
| Adversarial attacks on an oblivious recommender |
Konstantina Christakopoulou, Arindam Banerjee |
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code |
39 |
| A pareto-efficient algorithm for multiple objective optimization in e-commerce recommendation |
Xiao Lin, Hongjie Chen, Changhua Pei, Fei Sun, Xuanji Xiao, Hanxiao Sun, Yongfeng Zhang, Wenwu Ou, Peng Jiang |
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code |
37 |
| Personalized fairness-aware re-ranking for microlending |
Weiwen Liu, Jun Guo, Nasim Sonboli, Robin Burke, Shengyu Zhang |
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code |
36 |
| CB2CF: a neural multiview content-to-collaborative filtering model for completely cold item recommendations |
Oren Barkan, Noam Koenigstein, Eylon Yogev, Ori Katz |
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code |
34 |
| Adversarial tensor factorization for context-aware recommendation |
Huiyuan Chen, Jing Li |
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code |
30 |
| Designing for the better by taking users into account: a qualitative evaluation of user control mechanisms in (news) recommender systems |
Jaron Harambam, Dimitrios Bountouridis, Mykola Makhortykh, Joris Van Hoboken |
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code |
25 |
| Deep language-based critiquing for recommender systems |
Ga Wu, Kai Luo, Scott Sanner, Harold Soh |
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code |
21 |
| PAL: a position-bias aware learning framework for CTR prediction in live recommender systems |
Huifeng Guo, Jinkai Yu, Qing Liu, Ruiming Tang, Yuzhou Zhang |
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code |
20 |
| Addressing delayed feedback for continuous training with neural networks in CTR prediction |
Sofia Ira Ktena, Alykhan Tejani, Lucas Theis, Pranay Kumar Myana, Deepak Dilipkumar, Ferenc Huszár, Steven Yoo, Wenzhe Shi |
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code |
20 |
| A simple multi-armed nearest-neighbor bandit for interactive recommendation |
Javier SanzCruzado, Pablo Castells, Esther López |
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code |
20 |
| RecSys challenge 2019: session-based hotel recommendations |
Peter Knees, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Jens Adamczak, Gerard Paul Leyson, Philipp Monreal |
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code |
20 |
| Attribute-aware non-linear co-embeddings of graph features |
Ahmed Rashed, Josif Grabocka, Lars SchmidtThieme |
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code |
19 |
| Enhancing VAEs for collaborative filtering: flexible priors & gating mechanisms |
Daeryong Kim, Bongwon Suh |
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code |
19 |
| A deep learning system for predicting size and fit in fashion e-commerce |
AbdulSaboor Sheikh, Romain Guigourès, Evgenii Koriagin, Yuen King Ho, Reza Shirvany, Roland Vollgraf, Urs Bergmann |
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code |
18 |
| Fairness and discrimination in recommendation and retrieval |
Michael D. Ekstrand, Robin Burke, Fernando Diaz |
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code |
17 |
| Revisiting offline evaluation for implicit-feedback recommender systems |
Olivier Jeunen |
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code |
17 |
| Pace my race: recommendations for marathon running |
Jakim Berndsen, Barry Smyth, Aonghus Lawlor |
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code |
16 |
| PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy |
Erika Duriakova, Elias Z. Tragos, Barry Smyth, Neil Hurley, Francisco J. Peña, Panagiotis Symeonidis, James Geraci, Aonghus Lawlor |
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code |
15 |
| Latent factor models and aggregation operators for collaborative filtering in reciprocal recommender systems |
James Neve, Ivan Palomares |
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code |
14 |
| HybridSVD: when collaborative information is not enough |
Evgeny Frolov, Ivan V. Oseledets |
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code |
14 |
| Online learning to rank for sequential music recommendation |
Bruno L. Pereira, Alberto Ueda, Gustavo Penha, Rodrygo L. T. Santos, Nivio Ziviani |
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code |
13 |
| Leveraging post-click feedback for content recommendations |
Hongyi Wen, Longqi Yang, Deborah Estrin |
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code |
13 |
| Music cold-start and long-tail recommendation: bias in deep representations |
Andres Ferraro |
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code |
13 |
| Combining text summarization and aspect-based sentiment analysis of users' reviews to justify recommendations |
Cataldo Musto, Gaetano Rossiello, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro |
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code |
13 |
| Data mining for item recommendation in MOBA games |
Vladimir Araujo, Felipe Rios, Denis Parra |
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code |
13 |
| Deep generative ranking for personalized recommendation |
Huafeng Liu, Jingxuan Wen, Liping Jing, Jian Yu |
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code |
12 |
| User-centered evaluation of strategies for recommending sequences of points of interest to groups |
Daniel Herzog, Wolfgang Wörndl |
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code |
12 |
| A comparison of calibrated and intent-aware recommendations |
Mesut Kaya, Derek G. Bridge |
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code |
12 |
| Latent multi-criteria ratings for recommendations |
Pan Li, Alexander Tuzhilin |
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code |
12 |
| Collective embedding for neural context-aware recommender systems |
Felipe Soares Da Costa, Peter Dolog |
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code |
11 |
| Aligning daily activities with personality: towards a recommender system for improving wellbeing |
Mohammed Khwaja, Miquel Ferrer, Jesus Omana Iglesias, A. Aldo Faisal, Aleksandar Matic |
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code |
11 |
| PyRecGym: a reinforcement learning gym for recommender systems |
Bichen Shi, Makbule Gulcin Ozsoy, Neil Hurley, Barry Smyth, Elias Z. Tragos, James Geraci, Aonghus Lawlor |
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code |
11 |
| Time slice imputation for personalized goal-based recommendation in higher education |
Weijie Jiang, Zachary A. Pardos |
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code |
10 |
| How can they know that?: a study of factors affecting the creepiness of recommendations |
Helma Torkamaan, CatalinMihai Barbu, Jürgen Ziegler |
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code |
10 |
| FineNet: a joint convolutional and recurrent neural network model to forecast and recommend anomalous financial items |
YuChe Tsai, ChihYao Chen, ShaoLun Ma, PeiChi Wang, YouJia Chen, YuChieh Chang, ChengTe Li |
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code |
9 |
| A generative model for review-based recommendations |
Oren Sar Shalom, Guy Uziel, Amir Kantor |
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code |
9 |
| On the discriminative power of hyper-parameters in cross-validation and how to choose them |
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Claudio Pomo, Azzurra Ragone |
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code |
9 |
| Asymmetric Bayesian personalized ranking for one-class collaborative filtering |
Shan Ouyang, Lin Li, Weike Pan, Zhong Ming |
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code |
8 |
| Uplift-based evaluation and optimization of recommenders |
Masahiro Sato, Janmajay Singh, Sho Takemori, Takashi Sonoda, Qian Zhang, Tomoko Ohkuma |
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code |
8 |
| Quick and accurate attack detection in recommender systems through user attributes |
Mehmet Aktukmak, Yasin Yilmaz, Ismail Uysal |
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code |
8 |
| Multi-armed recommender system bandit ensembles |
Rocío Cañamares, Marcos Redondo, Pablo Castells |
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code |
8 |
| The influence of personal values on music taste: towards value-based music recommendations |
Sandy Manolios, Alan Hanjalic, Cynthia C. S. Liem |
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code |
7 |
| Explaining and exploring job recommendations: a user-driven approach for interacting with knowledge-based job recommender systems |
Francisco Gutiérrez, Sven Charleer, Robin De Croon, Nyi Nyi Htun, Gerd Goetschalckx, Katrien Verbert |
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code |
7 |
| User-centric evaluation of session-based recommendations for an automated radio station |
Malte Ludewig, Dietmar Jannach |
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code |
7 |
| RecTour 2019: workshop on recommenders in tourism |
Julia Neidhardt, Wolfgang Wörndl, Tsvi Kuflik, Markus Zanker, CatalinMihai Barbu |
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code |
7 |
| Recommendation in multistakeholder environments |
Robin Burke, Himan Abdollahpouri, Edward C. Malthouse, K. P. Thai, Yongfeng Zhang |
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code |
7 |
| Multi-stakeholder recommendations: case studies, methods and challenges |
Yong Zheng |
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code |
7 |
| Exploiting contextual information for recommender systems oriented to tourism |
Pablo Sánchez |
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code |
7 |
| Recommender system for developing new preferences and goals |
Yu Liang |
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code |
7 |
| Guiding creative design in online advertising |
Shaunak Mishra, Manisha Verma, Jelena Gligorijevic |
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code |
7 |
| Personalized diffusions for top-n recommendation |
Athanasios N. Nikolakopoulos, Dimitris Berberidis, George Karypis, Georgios B. Giannakis |
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code |
6 |
| Should we embed?: a study on the online performance of utilizing embeddings for real-time job recommendations |
Emanuel Lacic, Markus ReiterHaas, Tomislav Duricic, Valentin Slawicek, Elisabeth Lex |
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code |
6 |
| LORE: a large-scale offer recommendation engine with eligibility and capacity constraints |
Rahul Makhijani, Shreya Chakrabarti, Dale Struble, Yi Liu |
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code |
6 |
| Efficient privacy-preserving recommendations based on social graphs |
Aidmar Wainakh, Tim Grube, Jörg Daubert, Max Mühlhäuser |
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code |
6 |
| Style conditioned recommendations |
Murium Iqbal, Kamelia Aryafar, Timothy Anderton |
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code |
6 |
| Microsoft recommenders: tools to accelerate developing recommender systems |
Scott Graham, JunKi Min, Tao Wu |
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code |
6 |
| Recommendations in a marketplace |
Rishabh Mehrotra, Benjamin A. Carterette |
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code |
6 |
| Variational low rank multinomials for collaborative filtering with side-information |
Ehtsham Elahi, Wei Wang, Dave Ray, Aish Fenton, Tony Jebara |
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code |
5 |
| Music recommendations in hyperbolic space: an application of empirical bayes and hierarchical poincaré embeddings |
Timothy Schmeier, Joseph Chisari, Sam Garrett, Brett Vintch |
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code |
5 |
| Users in the loop: a psychologically-informed approach to similar item retrieval |
Amy A. Winecoff, Florin Brasoveanu, Bryce Casavant, Pearce Washabaugh, Matthew Graham |
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code |
5 |
| Predictability limits in session-based next item recommendation |
Priit Järv |
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code |
5 |
| Attribute-based evaluation for recommender systems: incorporating user and item attributes in evaluation metrics |
Pablo Sánchez, Alejandro Bellogín |
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code |
5 |
| Find my next job: labor market recommendations using administrative big data |
Snorre S. FridNielsen |
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code |
5 |
| Future of in-vehicle recommendation systems @ Bosch |
Juergen Luettin, Susanne Rothermel, Mark Andrew |
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code |
5 |
| AnnoMath TeX - a formula identifier annotation recommender system for STEM documents |
Philipp Scharpf, Ian Mackerracher, Moritz Schubotz, Jöran Beel, Corinna Breitinger, Bela Gipp |
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code |
5 |
| Domain adaptation in display advertising: an application for partner cold-start |
Karan Aggarwal, Pranjul Yadav, S. Sathiya Keerthi |
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code |
5 |
| Relaxed softmax for PU learning |
Ugo Tanielian, Flavian Vasile |
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code |
5 |
| PrivateJobMatch: a privacy-oriented deferred multi-match recommender system for stable employment |
Amar Saini, Florin Rusu, Andrew Johnston |
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code |
4 |
| Product collection recommendation in online retail |
Pigi Kouki, Ilias Fountalis, Nikolaos Vasiloglou, Nian Yan, Unaiza Ahsan, Khalifeh Al Jadda, Huiming Qu |
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code |
4 |
| Bandit algorithms in recommender systems |
Dorota Glowacka |
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code |
4 |
| A recommender system for heterogeneous and time sensitive environment |
Meng Wu, Ying Zhu, Qilian Yu, Bhargav Rajendra, Yunqi Zhao, Navid Aghdaie, Kazi A. Zaman |
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code |
4 |
| On gossip-based information dissemination in pervasive recommender systems |
Tobias Eichinger, Felix Beierle, Robin Papke, Lucas Rebscher, Hong Chinh Tran, Magdalena Trzeciak |
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code |
4 |
| Homepage personalization at spotify |
Oguz Semerci, Alois Gruson, Catherinee Edwards, Ben Lacker, Clay Gibson, Vladan Radosavljevic |
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code |
4 |
| Darwin & Goliath: a white-label recommender-system as-a-service with automated algorithm-selection |
Jöran Beel, Alan Griffin, Conor O'Shea |
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code |
4 |
| SMORe: modularize graph embedding for recommendation |
ChihMing Chen, TingHsiang Wang, ChuanJu Wang, MingFeng Tsai |
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code |
3 |
| DualDiv: diversifying items and explanation styles in explainable hybrid recommendation |
Kosetsu Tsukuda, Masataka Goto |
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code |
3 |
| Compositional network embedding for link prediction |
Tianshu Lyu, Fei Sun, Peng Jiang, Wenwu Ou, Yan Zhang |
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code |
3 |
| The trinity of luxury fashion recommendations: data, experts and experimentation |
Ana Rita Magalhães |
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code |
3 |
| Interactive evaluation of recommender systems with SNIPER: an episode mining approach |
Sandy Moens, Olivier Jeunen, Bart Goethals |
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code |
3 |
| StoryTime: eliciting preferences from children for book recommendations |
Ashlee Milton, Michael Green, Adam Keener, Joshua Ames, Michael D. Ekstrand, Maria Soledad Pera |
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code |
3 |
| Fourth international workshop on health recommender systems (HealthRecSys 2019) |
David Elsweiler, Bernd Ludwig, Alan Said, Hanna Schäfer, Helma Torkamaan, Christoph Trattner |
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code |
3 |
| Traversing semantically annotated queries for task-oriented query recommendation |
Arthur Câmara, Rodrygo L. T. Santos |
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code |
2 |
| From preference into decision making: modeling user interactions in recommender systems |
Qian Zhao, Martijn C. Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan |
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code |
2 |
| Efficient similarity computation for collaborative filtering in dynamic environments |
Olivier Jeunen, Koen Verstrepen, Bart Goethals |
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code |
2 |
| When actions speak louder than clicks: a combined model of purchase probability and long-term customer satisfaction |
Gal Lavee, Noam Koenigstein, Oren Barkan |
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code |
2 |
| Predicting online performance of job recommender systems with offline evaluation |
Adrien Mogenet, TuanAnh Nguyen Pham, Masahiro Kazama, Jialin Kong |
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code |
2 |
| Greedy optimized multileaving for personalization |
Kojiro Iizuka, Takeshi Yoneda, Yoshifumi Seki |
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code |
2 |
| Designer-driven add-to-cart recommendations |
Sandhya Sachidanandan, Richard Luong, Emil S. Joergensen |
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code |
2 |
| Whose data traces, whose voices? Inequality in online participation and why it matters for recommendation systems research |
Eszter Hargittai |
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code |
1 |
| Ghosting: contextualized inline query completion in large scale retail search |
Lakshmi Ramachandran, Uma Murthy |
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code |
1 |
| Towards interactive recommending in model-based collaborative filtering systems |
Benedikt Loepp, Jürgen Ziegler |
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code |
1 |
| ORSUM 2019 2nd workshop on online recommender systems and user modeling |
João Vinagre, Alípio Mário Jorge, Albert Bifet, Marie AlGhossein |
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code |
1 |
| Online ranking combination |
Erzsébet Frigó, Levente Kocsis |
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code |
1 |
| REVEAL 2019: closing the loop with the real world: reinforcement and robust estimators for recommendation |
Thorsten Joachims, Maria Dimakopoulou, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile |
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code |
1 |
| "Just play something awesome": the personalization powering voice interactions at Pandora |
Vito Claudio Ostuni |
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code |
1 |
| IRF: interactive recommendation through dialogue |
Oznur Alkan, Massimiliano Mattetti, Elizabeth M. Daly, Adi Botea, Inge Vejsbjerg |
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code |
1 |
| RecSys '19 joint workshop on 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 |
1 |
| Concept to code: deep learning for multitask recommendation |
Omprakash Sonie |
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code |
1 |
| ACM RecSys'19 late-breaking results (posters) |
Marko Tkalcic, Maria Soledad Pera |
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code |
1 |
| Incorporating intent propensities in personalized next best action recommendation |
Yuxi Zhang, Kexin Xie |
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code |
0 |
| Pick & merge: an efficient item filtering scheme for Windows store recommendations |
Adi Makmal, Jonathan Ephrath, Hilik Berezin, Liron I. Allerhand, Nir Nice, Noam Koenigstein |
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code |
0 |
| Recommender systems for contextually-aware, versioned items |
Yayu Zhou |
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code |
0 |
| Recommendation in home improvement industry, challenges and opportunities |
Khalifeh Al Jadda |
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code |
0 |
| Recommendation systems compliant with legal and editorial policies: the BBC+ app journey |
Maria Panteli |
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code |
0 |
| Driving content recommendations by building a knowledge base using weak supervision and transfer learning |
Sanghamitra Deb |
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code |
0 |
| Third workshop on recommendation in complex scenarios (ComplexRec 2019) |
Marijn Koolen, Toine Bogers, Bamshad Mobasher, Alexander Tuzhilin |
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code |
0 |
| First workshop on the impact of recommender systems at ACM RecSys 2019 |
Oren Sar Shalom, Dietmar Jannach, Ido Guy |
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code |
0 |
| The 7th international workshop on news recommendation and analytics (INRA 2019) |
Özlem Özgöbek, Benjamin Kille, Jon Atle Gulla, Andreas Lommatzsch |
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code |
0 |
| User's activity driven short-term context inference |
Miroslav Rac |
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code |
0 |
| Predicting user routines with masked dilated convolutions |
Renzhong Wang, Dragomir Yankov, Michael R. Evans, Senthil Palanisamy, Siddhartha Arora, Wei Wu |
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code |
0 |
| Using AI to build communities around interests on LinkedIn |
Abdulla AlQawasmeh, Ankan Saha |
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code |
0 |
| Rude awakenings from behaviourist dreams. Methodological integrity and the GDPR |
Mireille Hildebrandt |
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code |
0 |
| Groupon finally explains why we showed those offers |
Sasank Channapragada, Harshit Syal, Ibrahim Maali |
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code |
0 |