Accurate and visual video recommendation based on deep neural network

Fan Yang; Gangmin Li; Yong Yue; Terry R. Payne

doi:10.1109/ICCCS55155.2022.9846417

Accurate and visual video recommendation based on deep neural network

Fan Yang
, Gangmin Li
, Yong Yue
, Terry R. Payne

Institute for Research in Applicable Computing (IRAC)

Xi'an Jiaotong-Liverpool University
University of Liverpool

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › 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)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	278-283
Number of pages	6
ISBN (Electronic)	9781665450607
ISBN (Print)	9781665450614
DOIs	https://doi.org/10.1109/ICCCS55155.2022.9846417
Publication status	Published - 15 Aug 2022
Event	2022 7th International Conference on Computer and Communication Systems (ICCCS) - Wuhan Duration: 22 Apr 2022 → 25 Apr 2022

Publication series

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

Conference

Conference	2022 7th International Conference on Computer and Communication Systems (ICCCS)
City	Wuhan
Period	22/04/22 → 25/04/22
Other	2022 7th International Conference on Computer and Communication Systems (ICCCS) (22/04/2022-25/04/2022, Wuhan)

Keywords

data visualization
deep neural network
personalized recommendation
video recommendation

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Information Systems
Renewable Energy, Sustainability and the Environment
Control and Optimization

Access to Document

10.1109/ICCCS55155.2022.9846417

https://ieeexplore.ieee.org/document/9846417

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Yang, F., Li, G., Yue, Y., & Payne, T. R. (2022). Accurate and visual video recommendation based on deep neural network. In 2022 7th International Conference on Computer and Communication Systems (ICCCS) (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{3d7bd25ed6894c5cb81039e62aa2c4d9,

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 Payne, \{Terry R.\}",

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

year = "2022",

month = aug,

day = "15",

doi = "10.1109/ICCCS55155.2022.9846417",

language = "English",

isbn = "9781665450614",

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)",

address = "United States",

}

Yang, F, Li, G, Yue, Y & Payne, TR 2022, Accurate and visual video recommendation based on deep neural network. in 2022 7th International Conference on Computer and Communication Systems (ICCCS). 2022 7th International Conference on Computer and Communication Systems, ICCCS 2022, Institute of Electrical and Electronics Engineers Inc., pp. 278-283, 2022 7th International Conference on Computer and Communication Systems (ICCCS), Wuhan, 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). 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/Report/Conference proceeding › Conference contribution › 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 R.

PY - 2022/8/15

Y1 - 2022/8/15

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

UR - https://www.scopus.com/pages/publications/85136966416

U2 - 10.1109/ICCCS55155.2022.9846417

DO - 10.1109/ICCCS55155.2022.9846417

M3 - Conference contribution

SN - 9781665450614

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

SP - 278

EP - 283

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 7th International Conference on Computer and Communication Systems (ICCCS)

Y2 - 22 April 2022 through 25 April 2022

ER -

Yang F, Li G, Yue Y, Payne TR. Accurate and visual video recommendation based on deep neural network. In 2022 7th International Conference on Computer and Communication Systems (ICCCS). 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

Keywords

ASJC Scopus subject areas

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