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Beijing, China

Baifendian | Entity website


Baifendian | Entity website


Baifendian | Entity website

2000


Baifendian | Entity website

1542% A4313LED1LCD445995199549959997999ALED A6A6 APP


Zhu Y.-X.,University of Electronic Science and Technology of China | Lu L.-Y.,Hangzhou Normal University | Lu L.-Y.,University of Fribourg | Lu L.-Y.,Baifendian
Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China | Year: 2012

In this article, the existed evaluation metrics for recommender systems are reviewed and the new progresses in this field are summarized from four aspects: accuracy, diversity, novelty and coverage. The merits, weaknesses and applicable conditions of different evaluation metrics are analized. The focus is concentrated on the importance of rank and some representative rank-sensitive metrics. The user-centric recommender systems are discussed and some important open problems are outlined as future possible directions.

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