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A Time-Aware CNN-Based Personalized Recommender System
Joint Authors
Yang, Dan
Zhang, Jing
Wang, Sifeng
Zhang, XueDong
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-18
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Recommender system has received tremendous attention and has been studied by scholars in recent years due to its wide applications in different domains.
With the in-depth study and application of deep learning algorithms, deep neural network is gradually used in recommender systems.
The success of modern recommender system mainly depends on the understanding and application of the context of recommendation requests.
However, when leveraging deep learning algorithms for recommendation, the impact of context information such as recommendation time and location is often neglected.
In this paper, a time-aware convolutional neural network- (CNN-) based personalized recommender system TC-PR is proposed.
TC-PR actively recommends items that meet users’ interests by analyzing users’ features, items’ features, and users’ ratings, as well as users’ time context.
Moreover, we use Tensorflow distributed open source framework to implement the proposed time-aware CNN-based recommendation algorithm which can effectively solve the problems of large data volume, large model, and slow speed of recommender system.
The experimental results on the MovieLens-1m real dataset show that the proposed TC-PR can effectively solve the cold-start problem and greatly improve the speed of data processing and the accuracy of recommendation.
American Psychological Association (APA)
Yang, Dan& Zhang, Jing& Wang, Sifeng& Zhang, XueDong. 2019. A Time-Aware CNN-Based Personalized Recommender System. Complexity،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1133278
Modern Language Association (MLA)
Yang, Dan…[et al.]. A Time-Aware CNN-Based Personalized Recommender System. Complexity No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1133278
American Medical Association (AMA)
Yang, Dan& Zhang, Jing& Wang, Sifeng& Zhang, XueDong. A Time-Aware CNN-Based Personalized Recommender System. Complexity. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1133278
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133278