Recurrent Neural Networks with Top-k Gains for Session-based Recommendations | Proceedings of the 27th ACM International Conference on Information and Knowledge Management
%0 Conference Paper
%1 hidasi2018recurrent
%A Hidasi, Balázs
%A Karatzoglou, Alexandros
%B Proceedings of the 27th ACM International Conference on Information and Knowledge Management
%D 2018
%I ACM
%K gru4rec+
%R 10.1145/3269206.3271761
%T Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
%U https://doi.org/10.1145%2F3269206.3271761
@inproceedings{hidasi2018recurrent,
added-at = {2021-05-04T23:12:19.000+0200},
author = {Hidasi, Bal{\'{a}}zs and Karatzoglou, Alexandros},
biburl = {https://www.bibsonomy.org/bibtex/2b2b3b1a7941913bcdf0fdbe0e0f8f806/nosebrain},
booktitle = {Proceedings of the 27th {ACM} International Conference on Information and Knowledge Management},
description = {Recurrent Neural Networks with Top-k Gains for Session-based Recommendations | Proceedings of the 27th ACM International Conference on Information and Knowledge Management},
doi = {10.1145/3269206.3271761},
interhash = {c3850c976925a31114ed613994613826},
intrahash = {b2b3b1a7941913bcdf0fdbe0e0f8f806},
keywords = {gru4rec+},
month = oct,
publisher = {{ACM}},
timestamp = {2021-05-04T23:12:19.000+0200},
title = {Recurrent Neural Networks with Top-k Gains for Session-based Recommendations},
url = {https://doi.org/10.1145%2F3269206.3271761},
year = 2018
}