A Stream-based Resource for Multi-Dimensional Evaluation of Recommender Algorithms

Autor: Kille, B., Lommatzsch, A., Hopfgartner, F., Larson, M., Vries, A.P.d., Kando, N.

Publikováno v: Kando, N. (ed.), SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Shinjuku, Tokyo, Japan — August 07-11, 2017, 1257-1260. New York : ACM
STARTPAGE=1257;ENDPAGE=1260;TITLE=Kando, N. (ed.), SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Shinjuku, Tokyo, Japan — August 07-11, 2017
SIGIR
Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017
Kando, N. (ed.), SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Shinjuku, Tokyo, Japan — August 07-11, 2017, pp. 1257-1260

Recommender System research has evolved to focus on developing algorithms capable of high performance in online systems. This development calls for a new evaluation infrastructure that supports multi-dimensional evaluation of recommender systems. Tod

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e54f1b2e8e41a05a23bd1dc6d2a25be
http://hdl.handle.net/2066/176390