| Recurrent knowledge graph embedding for effective recommendation |
Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, LongKai Huang, Chi Xu |
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code |
152 |
| Deep reinforcement learning for page-wise recommendations |
Xiangyu Zhao, Long Xia, Liang Zhang, Zhuoye Ding, Dawei Yin, Jiliang Tang |
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code |
152 |
| Spectral collaborative filtering |
Lei Zheng, ChunTa Lu, Fei Jiang, Jiawei Zhang, Philip S. Yu |
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code |
98 |
| Causal embeddings for recommendation |
Stephen Bonner, Flavian Vasile |
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code |
90 |
| HOP-rec: high-order proximity for implicit recommendation |
JhengHong Yang, ChihMing Chen, ChuanJu Wang, MingFeng Tsai |
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code |
90 |
| Unbiased offline recommender evaluation for missing-not-at-random implicit feedback |
Longqi Yang, Yin Cui, Yuan Xuan, Chenyang Wang, Serge J. Belongie, Deborah Estrin |
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code |
88 |
| How algorithmic confounding in recommendation systems increases homogeneity and decreases utility |
Allison J. B. Chaney, Brandon M. Stewart, Barbara E. Engelhardt |
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code |
80 |
| Calibrated recommendations |
Harald Steck |
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code |
75 |
| Item recommendation on monotonic behavior chains |
Mengting Wan, Julian J. McAuley |
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code |
73 |
| Word2vec applied to recommendation: hyperparameters matter |
Hugo CasellesDupré, Florian Lesaint, Jimena RoyoLetelier |
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code |
64 |
| Explore, exploit, and explain: personalizing explainable recommendations with bandits |
James McInerney, Benjamin Lacker, Samantha Hansen, Karl Higley, Hugues Bouchard, Alois Gruson, Rishabh Mehrotra |
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code |
62 |
| Why I like it: multi-task learning for recommendation and explanation |
Yichao Lu, Ruihai Dong, Barry Smyth |
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code |
59 |
| Recsys challenge 2018: automatic music playlist continuation |
ChingWei Chen, Paul Lamere, Markus Schedl, Hamed Zamani |
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code |
54 |
| Translation-based factorization machines for sequential recommendation |
Rajiv Pasricha, Julian J. McAuley |
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code |
42 |
| Exploring author gender in book rating and recommendation |
Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, Daniel Kluver |
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code |
37 |
| On the robustness and discriminative power of information retrieval metrics for top-N recommendation |
Daniel Valcarce, Alejandro Bellogín, Javier Parapar, Pablo Castells |
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code |
32 |
| The art of drafting: a team-oriented hero recommendation system for multiplayer online battle arena games |
Zhengxing Chen, TruongHuy D. Nguyen, Yuyu Xu, Christopher Amato, Seth Cooper, Yizhou Sun, Magy Seif ElNasr |
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code |
32 |
| Multistakeholder recommendation with provider constraints |
Özge Sürer, Robin Burke, Edward C. Malthouse |
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code |
30 |
| RecGAN: recurrent generative adversarial networks for recommendation systems |
Homanga Bharadhwaj, Homin Park, Brian Y. Lim |
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code |
29 |
| Providing explanations for recommendations in reciprocal environments |
Akiva Kleinerman, Ariel Rosenfeld, Sarit Kraus |
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code |
27 |
| Quality-aware neural complementary item recommendation |
Yin Zhang, Haokai Lu, Wei Niu, James Caverlee |
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code |
26 |
| Effects of personal characteristics on music recommender systems with different levels of controllability |
Yucheng Jin, Nava Tintarev, Katrien Verbert |
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code |
25 |
| Streamingrec: a framework for benchmarking stream-based news recommenders |
Michael Jugovac, Dietmar Jannach, Mozhgan Karimi |
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code |
24 |
| Judging similarity: a user-centric study of related item recommendations |
Yuan Yao, F. Maxwell Harper |
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code |
23 |
| Harnessing a generalised user behaviour model for next-POI recommendation |
David Massimo, Francesco Ricci |
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code |
23 |
| Understanding user interactions with podcast recommendations delivered via voice |
Longqi Yang, Michael Sobolev, Christina Tsangouri, Deborah Estrin |
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code |
21 |
| Audio-visual encoding of multimedia content for enhancing movie recommendations |
Yashar Deldjoo, Mihai Gabriel Constantin, Hamid EghbalZadeh, Bogdan Ionescu, Markus Schedl, Paolo Cremonesi |
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code |
21 |
| Rank and rate: multi-task learning for recommender systems |
Guy Hadash, Oren Sar Shalom, Rita Osadchy |
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code |
20 |
| Attentive neural architecture incorporating song features for music recommendation |
Noveen Sachdeva, Kartik Gupta, Vikram Pudi |
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code |
20 |
| Decomposing fit semantics for product size recommendation in metric spaces |
Rishabh Misra, Mengting Wan, Julian J. McAuley |
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code |
19 |
| Adaptive collaborative topic modeling for online recommendation |
Marie AlGhossein, PierreAlexandre Murena, Talel Abdessalem, Anthony Barré, Antoine Cornuéjols |
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code |
17 |
| Semantic-based tag recommendation in scientific bookmarking systems |
Hebatallah A. Mohamed Hassan, Giuseppe Sansonetti, Fabio Gasparetti, Alessandro Micarelli |
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code |
17 |
| A hierarchical bayesian model for size recommendation in fashion |
Romain Guigourès, Yuen King Ho, Evgenii Koriagin, AbdulSaboor Sheikh, Urs Bergmann, Reza Shirvany |
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code |
17 |
| Preference elicitation as an optimization problem |
Anna Sepliarskaia, Julia Kiseleva, Filip Radlinski, Maarten de Rijke |
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code |
17 |
| Optimally balancing receiver and recommended users' importance in reciprocal recommender systems |
Akiva Kleinerman, Ariel Rosenfeld, Francesco Ricci, Sarit Kraus |
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code |
15 |
| User preference learning in multi-criteria recommendations using stacked auto encoders |
Dharahas Tallapally, Rama Syamala Sreepada, Bidyut Kr. Patra, Korra Sathya Babu |
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code |
15 |
| Tourrec: a tourist trip recommender system for individuals and groups |
Daniel Herzog, Christopher Laß, Wolfgang Wörndl |
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code |
15 |
| Trust-based collaborative filtering: tackling the cold start problem using regular equivalence |
Tomislav Duricic, Emanuel Lacic, Dominik Kowald, Elisabeth Lex |
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code |
14 |
| Enhancing structural diversity in social networks by recommending weak ties |
Javier SanzCruzado, Pablo Castells |
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code |
14 |
| CLoSe: Contextualized Location Sequence Recommender |
Ramesh Baral, S. S. Iyengar, Tao Li, N. Balakrishnan |
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code |
14 |
| Field-aware probabilistic embedding neural network for CTR prediction |
Weiwen Liu, Ruiming Tang, Jiajin Li, Jinkai Yu, Huifeng Guo, Xiuqiang He, Shengyu Zhang |
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code |
13 |
| Sustainability at scale: towards bridging the intention-behavior gap with sustainable recommendations |
Sabina Tomkins, Steven Isley, Ben London, Lise Getoor |
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code |
13 |
| Artwork personalization at netflix |
Fernando Amat Gil, Ashok Chandrashekar, Tony Jebara, Justin Basilico |
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code |
13 |
| Generation meets recommendation: proposing novel items for groups of users |
Thanh Vinh Vo, Harold Soh |
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code |
12 |
| Comfride: a smartphone based system for comfortable public transport recommendation |
Rohit Verma, Surjya Ghosh, Saketh Mahankali, Niloy Ganguly, Bivas Mitra, Sandip Chakraborty |
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code |
12 |
| Impact of item consumption on assessment of recommendations in user studies |
Benedikt Loepp, Tim Donkers, Timm Kleemann, Jürgen Ziegler |
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code |
11 |
| Categorical-attributes-based item classification for recommender systems |
Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed H. Chi |
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code |
11 |
| Eliciting pairwise preferences in recommender systems |
Saikishore Kalloori, Francesco Ricci, Rosella Gennari |
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code |
11 |
| Exploring recommendations under user-controlled data filtering |
Hongyi Wen, Longqi Yang, Michael Sobolev, Deborah Estrin |
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code |
9 |
| User preferences in recommendation algorithms: the influence of user diversity, trust, and product category on privacy perceptions in recommender algorithms |
Laura Burbach, Johannes Nakayama, Nils Plettenberg, Martina Ziefle, André Calero Valdez |
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code |
9 |
| Interpreting user inaction in recommender systems |
Qian Zhao, Martijn C. Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan |
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code |
9 |
| CHAMELEON: a deep learning meta-architecture for news recommender systems |
Gabriel de Souza Pereira Moreira |
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code |
9 |
| Mixed methods for evaluating user satisfaction |
Jean GarciaGathright, Christine Hosey, Brian St. Thomas, Ben Carterette, Fernando Diaz |
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code |
9 |
| Get me the best: predicting best answerers in community question answering sites |
Rohan Tondulkar, Manisha Dubey, Maunendra Sankar Desarkar |
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code |
9 |
| Knowledge-aware and conversational recommender systems |
Vito Walter Anelli, Pierpaolo Basile, Derek G. Bridge, Tommaso Di Noia, Pasquale Lops, Cataldo Musto, Fedelucio Narducci, Markus Zanker |
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code |
8 |
| Learning to recommend diverse items over implicit feedback on PANDOR |
Sumit Sidana, Charlotte Laclau, MassihReza Amini |
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code |
8 |
| Deep neural network marketplace recommenders in online experiments |
Simen Eide, Ning Zhou |
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code |
8 |
| Using citation-context to reduce topic drifting on pure citation-based recommendation |
Anita Khadka, Petr Knoth |
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code |
8 |
| Case recommender: a flexible and extensible python framework for recommender systems |
Arthur F. Da Costa, Eduardo P. Fressato, Fernando Soares de Aguiar Neto, Marcelo G. Manzato, Ricardo J. G. B. Campello |
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code |
8 |
| Multimedia recommender systems |
Yashar Deldjoo, Markus Schedl, Balázs Hidasi, Peter Knees |
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code |
8 |
| Video recommendation using crowdsourced time-sync comments |
Qing Ping |
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code |
8 |
| CF4CF: recommending collaborative filtering algorithms using collaborative filtering |
Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho |
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code |
7 |
| Kernelized probabilistic matrix factorization for collaborative filtering: exploiting projected user and item graph |
Bithika Pal, Mamata Jenamani |
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code |
7 |
| Interactive recommendation via deep neural memory augmented contextual bandits |
Yilin Shen, Yue Deng, Avik Ray, Hongxia Jin |
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code |
7 |
| Automating recommender systems experimentation with librec-auto |
Masoud Mansoury, Robin Burke, Aldo OrdonezGauger, Xavier Sepulveda |
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code |
7 |
| 2nd FATREC workshop: responsible recommendation |
Toshihiro Kamishima, PierreNicolas Schwab, Michael D. Ekstrand |
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code |
7 |
| Neural gaussian mixture model for review-based rating prediction |
Dong Deng, Liping Jing, Jian Yu, Shaolong Sun, Haofei Zhou |
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code |
7 |
| Module advisor: a hybrid recommender system for elective module exploration |
Nina Hagemann, Michael P. O'Mahony, Barry Smyth |
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code |
6 |
| Recommending social-interactive games for adults with autism spectrum disorders (ASD) |
YiuKai Ng, Maria Soledad Pera |
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code |
5 |
| Psrec: social recommendation with pseudo ratings |
Yitong Meng, Guangyong Chen, Jiajin Li, Shengyu Zhang |
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code |
5 |
| Sequence-aware recommendation |
Massimo Quadrana, Paolo Cremonesi |
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code |
5 |
| Testing a recommender system for self-actualization |
Daricia Wilkinson |
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code |
5 |
| Comparing recommender systems using synthetic data |
Manel Slokom |
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code |
5 |
| A crowdsourcing triage algorithm for geopolitical event forecasting |
Mohammad Rostami, David J. Huber, TsaiChing Lu |
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code |
5 |
| What's going on in my city?: recommender systems and electronic participatory budgeting |
Iván Cantador, María E. CortésCediel, Miriam Fernández, Harith Alani |
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code |
4 |
| No more ready-made deals: constructive recommendation for telco service bundling |
Paolo Dragone, Giovanni Pellegrini, Michele Vescovi, Katya Tentori, Andrea Passerini |
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code |
4 |
| REVEAL 2018: offline evaluation for recommender systems |
Thorsten Joachims, Adith Swaminathan, Yves Raimond, Olivier Koch, Flavian Vasile |
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code |
4 |
| Picture-based navigation for diagnosing post-harvest diseases of apple |
Maximilian Nocker, Gabriele Sottocornola, Markus Zanker, Sanja Baric, Greice Amaral Carneiro, Fabio Stella |
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code |
4 |
| Efficient online recommendation via low-rank ensemble sampling |
Xiuyuan Lu, Zheng Wen, Branislav Kveton |
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code |
3 |
| Learning consumer and producer embeddings for user-generated content recommendation |
WangCheng Kang, Julian J. McAuley |
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|
code |
3 |
| Hulu video recommendation: from relevance to reasoning |
Xiaoran Xu, Laming Chen, Songpeng Zu, Hanning Zhou |
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code |
3 |
| Query-based simple and scalable recommender systems with apache hivemall |
Takuya Kitazawa, Makoto Yui |
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code |
3 |
| A field study of related video recommendations: newest, most similar, or most relevant? |
Yifan Zhong, Tahir Lazaro Sousa Menezes, Vikas Kumar, Qian Zhao, F. Maxwell Harper |
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code |
3 |
| Large-scale recommendation for portfolio optimization |
Robin M. E. Swezey, Bruno Charron |
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code |
3 |
| Recommendations for chemists: a case study |
Steven L. Rohall, Margaret PancostHeidebrecht, Bill Shirley, Douglas Bacon, Michael A. Tarselli |
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code |
3 |
| Third international workshop on health recommender systems (healthrecsys 2018) |
David Elsweiler, Bernd Ludwig, Alan Said, Hanna Schäfer, Helma Torkamaan, Christoph Trattner |
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code |
3 |
| Concept to code: learning distributed representation of heterogeneous sources for recommendation |
Omprakash Sonie, Sudeshna Sarkar, Surender Kumar |
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code |
3 |
| Measuring anti-relevance: a study on when recommendation algorithms produce bad suggestions |
Pablo Sánchez, Alejandro Bellogín |
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code |
2 |
| Towards an open, collaborative REST API for recommender systems |
Iván García, Alejandro Bellogín |
|
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|
code |
2 |
| Beyond the top-N: algorithms that generate recommendations for self-actualization |
Lijie Guo |
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|
code |
2 |
| Extra: explaining team recommendation in networks |
Qinghai Zhou, Liangyue Li, Nan Cao, Norbou Buchler, Hanghang Tong |
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|
code |
2 |
| 2nd workshop on recommendation in complex scenarios (complexrec 2018) |
Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Casper Petersen |
|
|
|
code |
2 |
| ACM recsys workshop on recommenders in tourism (rectour 2018) |
Julia Neidhardt, Wolfgang Wörndl, Tsvi Kuflik, Markus Zanker |
|
|
|
code |
2 |
| Towards the next generation of multi-criteria recommender systems |
Zhe Li |
|
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|
code |
2 |
| Adapting session based recommendation for features through transfer learning |
Even Oldridge |
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|
code |
1 |
| SeRenA: a semantic recommender for all |
Giorgia Di Tommaso |
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|
code |
1 |
| Deep inventory time translation to improve recommendations for real-world retail |
Bobby Prévost, Jonathan Laflamme Janssen, Jaime R. Camacaro, Carolina Bessega |
|
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|
code |
1 |
| Measuring operational quality of recommendations: industry talk abstract |
Lina Weichbrodt |
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|
code |
1 |
| Conversational content discovery via comcast X1 voice interface |
Shahin Sefati, Parsa Saadatpanah, Hassan Sayyadi, Jan Neumann |
|
|
|
code |
1 |
| Recsys'18 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 |
| The 2nd workshop on intelligent recommender systems by knowledge transfer & learning (recsysKTL) |
Shaghayegh (Sherry) Sahebi, Yong Zheng, Weike Pan, Ignacio Fernández |
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code |
1 |
| Modularizing deep neural network-inspired recommendation algorithms |
Longqi Yang, Eugene Bagdasaryan, Hongyi Wen |
|
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|
code |
1 |
| Connecting sellers and buyers on the world's largest inventory |
Ido Guy |
|
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|
code |
1 |
| Hybrid search: incorporating contextual signals in recommendations at pinterest |
Jenny Liu |
|
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|
code |
0 |
| Variational learning to rank (VL2R) |
Keld T. Lundgaard |
|
|
|
code |
0 |
| Recommending social cohesion |
Christopher Berry |
|
|
|
code |
0 |
| Five E's: reflecting on the design of recommendations |
Elizabeth F. Churchill |
|
|
|
code |
0 |
| A probabilistic model for intrusive recommendation assessment |
Imen Akermi, Mohand Boughanem, Rim Faiz |
|
|
|
code |
0 |
| Learning content and usage factors simultaneously to reduce clickbaits |
Arnab Bhadury, Aanchan Mohan |
|
|
|
code |
0 |
| Building recommender systems with strict privacy boundaries |
Renaud Bourassa |
|
|
|
code |
0 |
| DLRS 2018: third workshop on deep learning for recommender systems |
Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman |
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|
code |
0 |
| Scalable structured prediction for richly structured socio-behavioral data |
Lise Getoor |
|
|
|
code |
0 |
| Learning within-session budgets from browsing trajectories |
Diane Hu, Raphael Louca, Liangjie Hong, Julian J. McAuley |
|
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|
code |
0 |
| Using textual summaries to describe a set of products |
Kittipitch Kuptavanich |
|
|
|
code |
0 |
| Cognitive company discovery |
Anuradha Bhamidipaty, Daniel M. Gruen, Justin Platz, John Vergo |
|
|
|
code |
0 |
| ACM recsys'18 late-breaking results (posters) |
Christoph Trattner, Vanessa Murdock, Shuo Chang |
|
|
|
code |
0 |