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Abstract:
the recommendation system is one of the core tasks of data mining. It divided into the recommendation system for explicit feedback and the recommendation system for implicit feedback. In recent years, many researchers have combined deep learning with recommendation system of explicit feedback and achieved excellent results. But it is very rare for implicit feedback. In this paper, we apply deep learning to the recommendation system for implicit feedback, and propose a new model that is combined with Neural Collaborative Filtering and Variable automatic-encoder. We use the MovieLens dataset to evaluate our proposed model. Experimental results show that the proposed model effectively improves the accuracy and quality of the recommended results, the Precision is 0.715 and the NDCG is 0.436 without manual parameters. © 2019 IEEE.
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Year: 2019
Page: 512-516
Language: English
Cited Count:
WoS CC Cited Count: 0
SCOPUS Cited Count: 3
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 3
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