RecSys Challenge 2015 and the YOOCHOOSE Dataset

By David Ben-Shimon, Alexander Tsikinovsky, Michael Friedmann, Bracha Shapira, Lior Rokach, J. Hörle. 2015

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How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks (2017, methodology): “The first dataset is publicly available YooChoose dataset [1] introduced for RecSys challenge 2015.”
Recurrent Latent Variable Networks for Session-Based Recommendation (2017, methodology): “he merits of our approach, in this Section we extensively evaluate it in challenging experimentalscenarios. Tothisend, weexploitthebenchmarkdatasetreleased in the context of the RecSys Challenge 2015 [3]; this comprises click-stream data pertaining to user sessions with an e-commerce website. Unfort”
RecSys Challenge 2015: ensemble learning with categorical features (2015, background): “RecSys Challenge 2015 [1] is organized around a typical example of such problem.”
A Survey on Session-based Recommender Systems (2019, unknown): “95 [5],[70],[132] Tmall2 1,774,729 13,418,695 425,348 7.”
A Time-Aware Exploration of RecSys15 Challenge Dataset (2016, background): “Thus, the release of the Yoo-choose Dataset for the RecSys Challenge 2015 [2] presents a major step forward on the research in e-commerce scenarios, being the ﬁrst dataset of this nature.”