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ORCIDRecSys 2019: Copenhagen, Denmark - Challenge
- Peter Knees, Yashar Deldjoo, Farshad Bakhshandegan Moghaddam, Jens Adamczak, Gerard Paul Leyson, Philipp Monreal:
Proceedings of the Workshop on ACM Recommender Systems Challenge, Copenhagen, Denmark, September 2019. ACM 2019, ISBN 978-1-4503-7667-9 - Pawel Jankiewicz, Liudmyla Kyrashchuk, Pawel Sienkowski, Magdalena Wójcik:
Boosting algorithms for a session-based, context-aware recommender system in an online travel domain. 1:1-1:5 - Maksims Volkovs, Anson Wong, Zhaoyue Cheng, Felipe Pérez, Ilya Stanevich, Yichao Lu:
Robust contextual models for in-session personalization. 2:1-2:5 - Zhe Wang, Yangbo Gao, Huan Chen, Peng Yan:
Session-based item recommendation with pairwise features. 3:1-3:5 - Kung-Hsiang Huang, Yi-Fu Fu, Yi-Ting Lee, Tzong-Hann Lee, Yao-Chun Chan, Yi-Hui Lee, Shou-De Lin:
A-HA: a hybrid approach for hotel recommendation. 4:1-4:5 - Malte Ludewig, Dietmar Jannach:
Learning to rank hotels for search and recommendation from session-based interaction logs and meta data. 5:1-5:5 - Ricardo Gama
, Hugo L. Fernandes:
An attentive RNN model for session-based and context-aware recommendations: a solution to the RecSys challenge 2019. 6:1-6:5 - Edoardo D'Amico, Giovanni Gabbolini, Daniele Montesi, Matteo Moreschini, Federico Parroni, Federico Piccinini, Alberto Rossettini, Alessio Russo Introito, Cesare Bernardis, Maurizio Ferrari Dacrema:
Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank. 7:1-7:5 - Sara Rabhi, Wenbo Sun, Julio Perez, Mads Ruben Burgdorff Kristensen, Jiwei Liu, Even Oldridge:
Accelerating recommender system training 15x with RAPIDS. 8:1-8:5 - Jaehoon Oh, Sangmook Kim, Se-Young Yun, Seungwoo Choi, Mun Yong Yi:
A pipelined hybrid recommender system for ranking the items on the display. 9:1-9:5
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