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CitRec 2017

Jie Yang, Zhu Sun, Alessandro Bozzon, Jie Zhang, Martha Larson
2017 Proceedings of the Eleventh ACM Conference on Recommender Systems - RecSys '17  
The "International Workshop on Recommender Systems for Citizens" (CitRec) is focused on a novel type of recommender systems both in terms of ownership and purpose: recommender systems run by citizens and  ...  Acknowledgments We thank the Social Urban Data Lab (SUDL) of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS) and Delft Data Science (DDS) for supporting the workshop.  ...  Thus they describe comprehensively citizens' behaviors and their relationships with the environment, providing opportunities for RecSys '17, August 27-31, 2017, Como, Italy Jie Yang, Zhu Sun, Alessandro  ... 
doi:10.1145/3109859.3109969 dblp:conf/recsys/YangSBZL17 fatcat:w7glpy4gmjfmvn6eccvl53i4ni

Folding

Doris Xin, Nicolas Mayoraz, Hubert Pham, Karthik Lakshmanan, John R. Anderson
2017 Proceedings of the Eleventh ACM Conference on Recommender Systems - RecSys '17  
In recommender systems based on low-rank factorization of a partially observed user-item matrix, a common phenomenon that plagues many otherwise e ective models is the interleaving of good and spurious  ...  A single spurious recommendation can dramatically impact the perceived quality of a recommender system.  ...  Algorithms II RecSys'17, August 27-31, 2017, Como, Italy In a typical recommender system powered by low-rank matrix factorization, the standard method for generating recommendations, after the embedding  ... 
doi:10.1145/3109859.3109911 dblp:conf/recsys/XinMPLA17 fatcat:yqbyemdj5vbmpdhwu5kp6hywvu

RecSys'17 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems

Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Nava Tintarev, Martijn Willemsen
2017 Proceedings of the Eleventh ACM Conference on Recommender Systems - RecSys '17  
This finding has the potential to improve the efficiency of data collection for applications such as Top-N recommender systems; where we are primarily interested in the ranked order of items, rather than  ...  We hypothesize that the issues arising from rater bias may be mitigated by treating the data received as an ordered set of preferences rather than a collection of absolute values.  ...  Researchers found that many respondents can be categorised as displaying one or more of these Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, August 27, 2017, Como, Italy  ... 
doi:10.1145/3109859.3109961 dblp:conf/recsys/BrusilovskyGFLO17 fatcat:vishcvo5jrdbnnj24ncydrbcfm

Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks

Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi
2017 Proceedings of the Eleventh ACM Conference on Recommender Systems - RecSys '17  
Results on two industry datasets show large improvements over the session-only RNNs.  ...  Session-based recommendations are highly relevant in many modern on-line services (e.g. e-commerce, video streaming) and recommendation settings.  ...  RecSys'17, August 27-31, 2017, Como, Italy. © 2017 ACM. 978-1-4503-4652-8/17/08. . . $15.00 DOI: http://dx.doi.org/10.1145/3109859.3109896 Formally, for each session S m = {i m,1 , i m,2 , ..., i m,  ... 
doi:10.1145/3109859.3109896 dblp:conf/recsys/QuadranaKHC17 fatcat:zlizm2zazjgilgojsfunlb7rwm

Metalearning for Context-aware Filtering

Tiago Cunha, Carlos Soares, André C.P.L.F. Carvalho
2017 Proceedings of the Eleventh ACM Conference on Recommender Systems - RecSys '17  
on new problems is the development of useful measures able to characterize the data, i.e. metafeatures.  ...  is work addresses the problem of selecting Tensor Factorization algorithms for the Context-aware Filtering recommendation task using a metalearning approach. e most important challenge of applying metalearning  ...  ACKNOWLEDGEMENTS is work is nanced by the ERDF Fund through the Operational Program for Competitiveness and Internationalization -COMPETE 2020 of Portugal 2020 through the National Innovation Agency (ANI  ... 
doi:10.1145/3109859.3109899 dblp:conf/recsys/0001SC17 fatcat:mt5ybgongrhv3fjhxmusukoidi