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ORCIDDLRS@RecSys 2017: Como, Italy
- Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk:
Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, DLRS@RecSys 2017, Como, Italy, August 27, 2017. ACM 2017, ISBN 978-1-4503-5353-3
Keynote
- Dit-Yan Yeung:
Keynote: Bayesian Deep Learning Models for Recommendation Applications. 1
Regular papers
- Elena Smirnova, Flavian Vasile:
Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks. 2-9 - Thomas Nedelec, Elena Smirnova, Flavian Vasile:
Specializing Joint Representations for the task of Product Recommendation. 10-18 - Ladislav Peska, Hana Trojanova:
Towards Recommender Systems for Police Photo Lineup. 19-23 - Massimiliano Ruocco, Ole Steinar Lillestøl Skrede, Helge Langseth:
Inter-Session Modeling for Session-Based Recommendation. 24-31 - Sergio Oramas, Oriol Nieto, Mohamed Sordo, Xavier Serra
:
A Deep Multimodal Approach for Cold-start Music Recommendation. 32-37 - Sotirios P. Chatzis, Panayiotis Christodoulou, Andreas S. Andreou:
Recurrent Latent Variable Networks for Session-Based Recommendation. 38-45 - Andreu Vall, Hamid Eghbal-zadeh, Matthias Dorfer, Markus Schedl, Gerhard Widmer:
Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features: Alleviating the Cold-Start Problem for Rare and Out-of-Set Songs. 46-54
Poster papers
- Vicente Dominguez, Pablo Messina, Denis Parra, Domingo Mery, Christoph Trattner, Alvaro Soto:
Comparing Neural and Attractiveness-based Visual Features for Artwork Recommendation. 55-59 - Vito Bellini, Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio:
Auto-Encoding User Ratings via Knowledge Graphs in Recommendation Scenarios. 60-66
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