Accurate and Visual Video Recommendation Based on Deep Neural Network

Fan Yang; Gangmin Li; Yong Yue; Terry Payne

doi:10.1109/ICCCS55155.2022.9846417

Accurate and Visual Video Recommendation Based on Deep Neural Network

Fan Yang
, Gangmin Li
, Yong Yue
, Terry Payne

Department of Computing

Xi'an Jiaotong-Liverpool University
University of Liverpool
University of Bedfordshire

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

2 Citations (Scopus)

Abstract

Video 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.

Original language	English
Title of host publication	2022 7th International Conference on Computer and Communication Systems, ICCCS 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	278-283
Number of pages	6
ISBN (Electronic)	9781665450607
DOIs	https://doi.org/10.1109/ICCCS55155.2022.9846417
Publication status	Published - 2022
Event	7th International Conference on Computer and Communication Systems, ICCCS 2022 - Wuhan, China Duration: 22 Apr 2022 → 25 Apr 2022

Publication series

Name	2022 7th International Conference on Computer and Communication Systems, ICCCS 2022

Conference

Conference	7th International Conference on Computer and Communication Systems, ICCCS 2022
Country/Territory	China
City	Wuhan
Period	22/04/22 → 25/04/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

data visualization
deep neural network
personalized recommendation
video recommendation

Access to Document

10.1109/ICCCS55155.2022.9846417

Cite this

Yang, F., Li, G., Yue, Y., & Payne, T. (2022). Accurate and Visual Video Recommendation Based on Deep Neural Network. In 2022 7th International Conference on Computer and Communication Systems, ICCCS 2022 (pp. 278-283). (2022 7th International Conference on Computer and Communication Systems, ICCCS 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCS55155.2022.9846417

@inproceedings{c5d09ad940d645e88206eaa4e18303cd,

title = "Accurate and Visual Video Recommendation Based on Deep Neural Network",

abstract = "Video 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.",

keywords = "data visualization, deep neural network, personalized recommendation, video recommendation",

author = "Fan Yang and Gangmin Li and Yong Yue and Terry Payne",

note = "Funding Information: ACKNOWLEDGMENT This 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). Publisher Copyright: {\textcopyright} 2022 IEEE.; 7th International Conference on Computer and Communication Systems, ICCCS 2022 ; Conference date: 22-04-2022 Through 25-04-2022",

year = "2022",

doi = "10.1109/ICCCS55155.2022.9846417",

language = "English",

series = "2022 7th International Conference on Computer and Communication Systems, ICCCS 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "278--283",

booktitle = "2022 7th International Conference on Computer and Communication Systems, ICCCS 2022",

}

Yang, F, Li, G , Yue, Y & Payne, T 2022, Accurate and Visual Video Recommendation Based on Deep Neural Network. in 2022 7th International Conference on Computer and Communication Systems, ICCCS 2022. 2022 7th International Conference on Computer and Communication Systems, ICCCS 2022, Institute of Electrical and Electronics Engineers Inc., pp. 278-283, 7th International Conference on Computer and Communication Systems, ICCCS 2022, Wuhan, China, 22/04/22. https://doi.org/10.1109/ICCCS55155.2022.9846417

Accurate and Visual Video Recommendation Based on Deep Neural Network. / Yang, Fan; Li, Gangmin ; Yue, Yong et al.
2022 7th International Conference on Computer and Communication Systems, ICCCS 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 278-283 (2022 7th International Conference on Computer and Communication Systems, ICCCS 2022).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Accurate and Visual Video Recommendation Based on Deep Neural Network

AU - Yang, Fan

AU - Li, Gangmin

AU - Yue, Yong

AU - Payne, Terry

N1 - Funding Information: ACKNOWLEDGMENT This 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). Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - Video 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.

AB - Video 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.

KW - data visualization

KW - deep neural network

KW - personalized recommendation

KW - video recommendation

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U2 - 10.1109/ICCCS55155.2022.9846417

DO - 10.1109/ICCCS55155.2022.9846417

M3 - Conference Proceeding

AN - SCOPUS:85136966416

T3 - 2022 7th International Conference on Computer and Communication Systems, ICCCS 2022

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BT - 2022 7th International Conference on Computer and Communication Systems, ICCCS 2022

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Yang F, Li G , Yue Y, Payne T. Accurate and Visual Video Recommendation Based on Deep Neural Network. In 2022 7th International Conference on Computer and Communication Systems, ICCCS 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 278-283. (2022 7th International Conference on Computer and Communication Systems, ICCCS 2022). doi: 10.1109/ICCCS55155.2022.9846417

Accurate and Visual Video Recommendation Based on Deep Neural Network

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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