Accurate and visual video recommendation based on deep neural network
deep neural network
Subject Categories::G730 Neural Computing
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AbstractVideo recommendation is vital for a video platform, which provides its users with videos they may be interested in. In this paper, we integrate users' ratings of videos in the video platform and community and crucial information data such as video category, director/actor, predict users' preference for videos through deep neural network, which could improve the accuracy of personalized recommendation. In addition, we use weighted force-directed Graph to show the relationship among users, videos, directors, and other elements, which could display the visualization of data elements and recommended results. Extensive experiments are conducted on three video datasets, and the experimental results demonstrate that the proposed method is more effective than several other recommendation methods.
CitationYang F, Li G, Yue Y, Payne T (2022) 'Accurate and visual video recommendation based on deep neural network', 2022 7th International Conference on Computer and Communication Systems (ICCCS) - Wuhan, Institute of Electrical and Electronics Engineers Inc..
TypeConference papers, meetings and proceedings
SponsorsThis work is supported by the Basic Public Welfare Research Project of Zhejiang (LGF20G020001), Key Lab of Film and TV Media Technology of Zhejiang Province (No.2020E10015), and the AI University Research Centre (AI URC) through the XJTLU Key Program Special Fund (KSF-A 17).