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ORCIDRecSys 2017: Como, Italy
- Paolo Cremonesi, Francesco Ricci, Shlomo Berkovsky, Alexander Tuzhilin:
Proceedings of the Eleventh ACM Conference on Recommender Systems, RecSys 2017, Como, Italy, August 27-31, 2017. ACM 2017, ISBN 978-1-4503-4652-8
Invited Keynotes
- George Loewenstein:
Recommender Systems and the New New Economics of Information. 1 - George Karypis
:
Improving Higher Education: Learning Analytics & Recommender Systems Research. 2 - Ronny Lempel:
Personalization is a Two-Way Street. 3 - Jason Weston:
Memory Networks for Recommendation. 4
Paper Session 1: Ranking
- Dimitrios Rafailidis, Fabio Crestani:
Learning to Rank with Trust and Distrust in Recommender Systems. 5-13 - Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho:
Metalearning for Context-aware Filtering: Selection of Tensor Factorization Algorithms. 14-22 - Yue Ning, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan:
A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. 23-31 - Enrico Palumbo, Giuseppe Rizzo, Raphaël Troncy:
entity2rec: Learning User-Item Relatedness from Knowledge Graphs for Top-N Item Recommendation. 32-36 - A. Murat Yagci, Tevfik Aytekin, Fikret S. Gürgen:
On Parallelizing SGD for Pairwise Learning to Rank in Collaborative Filtering Recommender Systems. 37-41 - Himan Abdollahpouri, Robin Burke, Bamshad Mobasher:
Controlling Popularity Bias in Learning-to-Rank Recommendation. 42-46
Paper Session 2: Human Interaction
- Jakub Macina, Ivan Srba, Joseph Jay Williams, Mária Bieliková:
Educational Question Routing in Online Student Communities. 47-55 - Kevin Jasberg, Sergej Sizov:
The Magic Barrier Revisited: Accessing Natural Limitations of Recommender Assessment. 56-64 - Alain Starke, Martijn C. Willemsen, Chris Snijders:
Effective User Interface Designs to Increase Energy-efficient Behavior in a Rasch-based Energy Recommender System. 65-73 - Rus M. Mesas, Alejandro Bellogín:
Evaluating Decision-Aware Recommender Systems. 74-78 - Behnoush Abdollahi, Olfa Nasraoui:
Using Explainability for Constrained Matrix Factorization. 79-83 - Pigi Kouki, James Schaffer, Jay Pujara, John O'Donovan, Lise Getoor:
User Preferences for Hybrid Explanations. 84-88
Paper Session 3: Unbiased and Private
- Erez Shmueli, Tamir Tassa:
Secure Multi-Party Protocols for Item-Based Collaborative Filtering. 89-97 - Xiaoying Zhang, Junzhou Zhao, John C. S. Lui:
Modeling the Assimilation-Contrast Effects in Online Product Rating Systems: Debiasing and Recommendations. 98-106 - Xiao Lin, Min Zhang, Yongfeng Zhang, Zhaoquan Gu, Yiqun Liu, Shaoping Ma:
Fairness-Aware Group Recommendation with Pareto-Efficiency. 107-115 - Barry Smyth, Pádraig Cunningham:
A Novel Recommender System for Helping Marathoners to Achieve a New Personal-Best. 116-120
Paper Session 6: Session-Based Recommender Systems
- Elena Viorica Epure, Benjamin Kille, Jon Espen Ingvaldsen, Rébecca Deneckère, Camille Salinesi, Sahin Albayrak:
Recommending Personalized News in Short User Sessions. 121-129 - Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi:
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. 130-137 - Trinh Xuan Tuan, Tu Minh Phuong:
3D Convolutional Networks for Session-based Recommendation with Content Features. 138-146 - Pablo Loyola, Chen Liu, Yu Hirate:
Modeling User Session and Intent with an Attention-based Encoder-Decoder Architecture. 147-151
Paper Session 7: Algorithms I
- Tim Donkers, Benedikt Loepp, Jürgen Ziegler:
Sequential User-based Recurrent Neural Network Recommendations. 152-160 - Ruining He, Wang-Cheng Kang, Julian J. McAuley:
Translation-based Recommendation. 161-169 - Rasaq Otunba, Raimi A. Rufai, Jessica Lin:
MPR: Multi-Objective Pairwise Ranking. 170-178 - Sebastian Prillo:
An Elementary View on Factorization Machines. 179-183
Paper Session 8: Algorithms II
- Deborah Cohen, Michal Aharon, Yair Koren, Oren Somekh, Raz Nissim:
Expediting Exploration by Attribute-to-Feature Mapping for Cold-Start Recommendations. 184-192 - Xixi Du, Huafeng Liu, Liping Jing:
Additive Co-Clustering with Social Influence for Recommendation. 193-200 - Doris Xin, Nicolas Mayoraz, Hubert Pham, Karthik Lakshmanan, John R. Anderson:
Folding: Why Good Models Sometimes Make Spurious Recommendations. 201-209 - John Savage, Akihiro Kishimoto, Beat Buesser, Ernesto Diaz-Aviles, Carlos Alzate:
Chemical Reactant Recommendation Using a Network of Organic Chemistry. 210-214
Paper Session 9: Diversity
- Bibek Paudel, Thilo Haas, Abraham Bernstein:
Fewer Flops at the Top: Accuracy, Diversity, and Regularization in Two-Class Collaborative Filtering. 215-223 - Jungkyu Han, Hayato Yamana:
Geographical Diversification in POI Recommendation: Toward Improved Coverage on Interested Areas. 224-228
Paper Session 10: Conversations
- Jie Kang, Kyle Condiff, Shuo Chang, Joseph A. Konstan, Loren G. Terveen, F. Maxwell Harper:
Understanding How People Use Natural Language to Ask for Recommendations. 229-237 - Toine Bogers, Marijn Koolen:
Defining and Supporting Narrative-driven Recommendation. 238-242
Paper Session 11: Novel and Practical
- Vivek Sembium, Rajeev Rastogi, Atul Saroop, Srujana Merugu:
Recommending Product Sizes to Customers. 243-250 - Antonino Freno:
Practical Lessons from Developing a Large-Scale Recommender System at Zalando. 251-259 - Raul Sanchez-Vazquez, Jordan Silva, Rodrygo L. T. Santos:
Exploiting Socio-Economic Models for Lodging Recommendation in the Sharing Economy. 260-268 - Jennifer Marlow, Jason Wiese:
Surveying User Reactions to Recommendations Based on Inferences Made by Face Detection Technology. 269-273 - Maleeha Qazi, Glenn Moo Fung, Katie J. Meissner, Eduardo R. Fontes:
An Insurance Recommendation System Using Bayesian Networks. 274-278
Paper Session 12: Deep Learning
- Joan Serrà, Alexandros Karatzoglou:
Getting Deep Recommenders Fit: Bloom Embeddings for Sparse Binary Input/Output Networks. 279-287 - Rose Catherine, William W. Cohen:
TransNets: Learning to Transform for Recommendation. 288-296 - Sungyong Seo, Jing Huang, Hao Yang, Yan Liu:
Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction. 297-305 - Dietmar Jannach, Malte Ludewig:
When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation. 306-310 - Debanjan Paul, Sudeshna Sarkar, Muthusamy Chelliah, Chetan Kalyan, Prajit Prashant Sinai Nadkarni:
Recommendation of High Quality Representative Reviews in e-commerce. 311-315
Paper Session 13: Semantics and Sentiment
- Hossein Rahmatizadeh Zagheli, Hamed Zamani, Azadeh Shakery:
A Semantic-Aware Profile Updating Model for Text Recommendation. 316-320 - Cataldo Musto, Marco de Gemmis, Giovanni Semeraro, Pasquale Lops:
A Multi-criteria Recommender System Exploiting Aspect-based Sentiment Analysis of Users' Reviews. 321-325 - Mehdi Elahi, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Leonardo Cella, Stefano Cereda, Paolo Cremonesi:
Exploring the Semantic Gap for Movie Recommendations. 326-330 - Yang Zhang, Chenwei Zhang, Xiaozhong Liu:
Dynamic Scholarly Collaborator Recommendation via Competitive Multi-Agent Reinforcement Learning. 331-335
Industry Session 1: Games and Travel
- Noam Koenigstein:
Rethinking Collaborative Filtering: A Practical Perspective on State-of-the-art Research Based on Real World Insights. 336-337 - Meng Wu, John Kolen, Navid Aghdaie, Kazi A. Zaman:
Recommendation Applications and Systems at Electronic Arts. 338 - Mihajlo Grbovic:
Search Ranking And Personalization at Airbnb. 339-340 - Neal Lathia:
Bootstrapping a Destination Recommender System. 341
Industry Session 2: Interesting Domains
- Justin Basilico, Yves Raimond:
Déjà Vu: The Importance of Time and Causality in Recommender Systems. 342 - Nick Landia:
Building Recommender Systems for Fashion: Industry Talk Abstract. 343 - João Gomes:
Boosting Recommender Systems with Deep Learning. 344 - Roberto Turrin:
Personalization challenges in e-Learning. 345 - Krishnaram Kenthapadi, Benjamin Le, Ganesh Venkataraman:
Personalized Job Recommendation System at LinkedIn: Practical Challenges and Lessons Learned. 346-347
Industry Session 3: Algorithms@Industry
- Daan Odijk, Anne Schuth:
Online Learning to Rank for Recommender Systems. 348 - Björn Brodén, Mikael Hammar, Bengt J. Nilsson, Dimitris Paraschakis:
Bandit Algorithms for e-Commerce Recommender Systems: Extended Abstract. 349 - Zhixian Yan, Lai Wei, Yunshan Lu, Zhongqiang Wu, Bo Tao:
You are what apps you use: Transfer Learning for Personalized Content and Ad Recommendation. 350
Demonstrations
- Panagiotis Symeonidis, Stergios Chairistanidis:
CheckInShop.eu: A Sensor-based Recommender System for micro-location Marketing. 351-352 - Marko Tkalcic, Nima Maleki, Matevz Pesek, Mehdi Elahi, Francesco Ricci, Matija Marolt:
A Research Tool for User Preferences Elicitation with Facial Expressions. 353-354 - Martin Boissier, Rainer Schlosser, Nikolai Podlesny, Sebastian Serth, Marvin Bornstein, Johanna Latt, Jan Lindemann, Jan Selke, Matthias Uflacker:
Data-Driven Repricing Strategies in Competitive Markets: An Interactive Simulation Platform. 355-357 - Francesco Corcoglioniti, Claudio Giuliano, Yaroslav Nechaev, Roberto Zanoli:
Pokedem: an Automatic Social Media Management Application. 358-359 - Malte Schwarzer, Corinna Breitinger, Moritz Schubotz, Norman Meuschke, Bela Gipp:
Citolytics: A Link-based Recommender System for Wikipedia. 360-361 - Ludovik Çoba, Panagiotis Symeonidis, Markus Zanker:
Visual Analysis of Recommendation Performance. 362-363 - Dawei Chen, Dongwoo Kim, Lexing Xie, Minjeong Shin, Aditya Krishna Menon, Cheng Soon Ong, Iman Avazpour, John Grundy:
PathRec: Visual Analysis of Travel Route Recommendations. 364-365
Workshops and Challenge
- Yong Zheng, Weike Pan, Shaghayegh (Sherry) Sahebi, Ignacio Fernández:
The 1st Workshop on Intelligent Recommender Systems by Knowledge Transfer & Learning: (RecSysKTL). 366-367 - Mária Bieliková, Veronika Bogina, Tsvi Kuflik, Roy Sasson:
The 1st International Workshop on Temporal Reasoning in Recommender Systems. 368-369 - Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk:
DLRS 2017: Second Workshop on Deep Learning for Recommender Systems. 370-371 - Fabian Abel, Yashar Deldjoo, Mehdi Elahi, Daniel Kohlsdorf:
RecSys Challenge 2017: Offline and Online Evaluation. 372-373 - David Elsweiler, Santiago Hors-Fraile, Bernd Ludwig, Alan Said, Hanna Schäfer, Christoph Trattner, Helma Torkamaan, André Calero Valdez:
Second Workshop on Health Recommender Systems: (HealthRecSys 2017). 374-375 - Jerry Alan Fails, Maria Soledad Pera, Franca Garzotto, Mirko Gelsomini:
KidRec: Children & Recommender Systems: Workshop Co-located with ACM Conference on Recommender Systems (RecSys 2017). 376-377 - Robin Burke, Gediminas Adomavicius, Ido Guy, Jan Krasnodebski, Luiz Augusto Pizzato, Yi Zhang, Himan Abdollahpouri:
VAMS 2017: Workshop on Value-Aware and Multistakeholder Recommendation. 378-379 - Toine Bogers, Marijn Koolen, Bamshad Mobasher, Alan Said, Alexander Tuzhilin:
Workshop on Recommendation in Complex Scenarios: (ComplexRec 2017). 380-381 - Michael D. Ekstrand, Amit Sharma:
FATREC Workshop on Responsible Recommendation. 382-383 - Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Nava Tintarev, Martijn C. Willemsen:
RecSys'17 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems. 384-385 - Julia Neidhardt, Daniel R. Fesenmaier, Tsvi Kuflik, Wolfgang Wörndl:
RecTour 2017: Workshop on Recommenders in Tourism. 386-387 - Jie Yang, Zhu Sun, Alessandro Bozzon, Jie Zhang, Martha A. Larson:
CitRec 2017: International Workshop on Recommender Systems for Citizens. 388-389 - Tao Ye, Denis Parra, Vito Ostuni, Tao Wang:
LSRS'17: Workshop on Large-Scale Recommender Systems. 390-391
Tutorials
- Markus Schedl, Peter Knees, Fabien Gouyon:
New Paths in Music Recommender Systems Research. 392-393 - Bart P. Knijnenburg, Shlomo Berkovsky:
Privacy for Recommender Systems: Tutorial Abstract. 394-395 - Alexandros Karatzoglou, Balázs Hidasi:
Deep Learning for Recommender Systems. 396-397 - Muthusamy Chelliah, Sudeshna Sarkar:
Product Recommendations Enhanced with Reviews. 398-399 - Róbert Pálovics, Domokos Kelen, András A. Benczúr:
Tutorial on Open Source Online Learning Recommenders. 400-401
Doctoral Symposiums
- Daniel Herzog:
Recommending a Sequence of Points of Interest to a Group of Users in a Mobile Context. 402-406 - Shatha Jaradat:
Deep Cross-Domain Fashion Recommendation. 407-410 - Rodrigo Zenun Franco:
Online Recommender System for Personalized Nutrition Advice. 411-415 - Özge Sürer:
Improving Similarity Measures Using Ontological Data. 416-420 - Raoua Abdelkhalek:
Improving the Trustworthiness of Recommendations in Collaborative Filtering under the Belief Function Framework. 421-425 - Francisco J. Peña:
Unsupervised Context-Driven Recommendations Based On User Reviews. 426-430 - Andrea Barraza-Urbina:
The Exploration-Exploitation Trade-off in Interactive Recommender Systems. 431-435 - Peter Gaspar:
User Preferences Analysis Using Visual Stimuli. 436-440 - Paolo Dragone:
Constructive Recommendation. 441-445
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