Operation and algorithm optimization of short video recommendation algorithm

Research Article
Open access

Operation and algorithm optimization of short video recommendation algorithm

Yilin Wu 1
  • 1 Wuxi No.1 High School, Wuxi, 214044, China    
  • *corresponding author
ACE Vol.4
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-915371-55-3
ISBN (Online): 978-1-915371-56-0

Abstract

Now that technology is developing rapidly, the field of computing has been showing exponential progress, and scientific and technological civilization of mankind is making continuous progress. Games, live broadcasts, and short videos are all new products under big data. Especially for short videos, the huge database records the preferences of billions of users. With the combination of collaborative filtering algorithms and content-based recommendation algorithms, computers can always accurately recommend suitable videos to various users. In this paper, improvement of this method is aimed at the item-based algorithm in the collaborative filtering algorithm. For the item-attribute matrix, first, use the Jaccard distance to calculate the similarity, and then use this similarity value instead of the Euler distance formula to bring it into the k-means clustering, and use iteration to obtain countless different clusters. Finally, set a threshold x, which is the distance between each cluster center. Whenever there is a new matrix to be classified, the similarity y corresponding to this matrix is calculated first. If y<x, the matrix is classified into the corresponding cluster. This approach can improve the diversity of recommended videos and tap the potential interests of users. Such improvements to the matrix can improve the accuracy of the algorithm and user stickiness.

Keywords:

Collaborative Filtering, Recommendation System, K-means, Jaccard Distance, Clustering, Matrix.

Wu,Y. (2023). Operation and algorithm optimization of short video recommendation algorithm. Applied and Computational Engineering,4,651-656.
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References

[1]. LIU Duan-yang. Design and implementation of video recommendation system based on deep viewing interest network. China Academic Journal Electric Publishing House, 2021.6.1, 18,19

[2]. LIU Xian-feng, LIU Tong-cun. Research on project grading prediction and recommendation algorithm based on attribute clustering, 2021,9,10,11

[3]. SU Kai, ZHANG Xuan, FU jin. Collaborative filtering algorithm based on attribute clustering and similarity optimization. China Academic Journal Electric Publishing House, 2021,11,30, 3,4

[4]. SUN Hong-mei. Research on Optimization of Collaborative Filtering. Algorithm.China Academic Journal Electric Publishing House,2021.5.1,1

[5]. WEN Feng-ming, XIE Fang-xue, Operational logic and ethical concerns of short video recommendation algorithms,China Academic Journal Electric Publishing House,2021.8.6,2

[6]. GU Ming-xing, Huang Wei-jian, Huang yuan.Collaborative filtering recommendation combining attribute clustering and improving user similarity,2020, 187,188,189

Cite this article

Wu,Y. (2023). Operation and algorithm optimization of short video recommendation algorithm. Applied and Computational Engineering,4,651-656.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

ISBN：978-1-915371-55-3(Print) / 978-1-915371-56-0(Online)
Editor：Omer Burak Istanbullu
Conference website: http://www.confspml.org
Conference date: 25 February 2023
Series: Applied and Computational Engineering
Volume number: Vol.4
ISSN：2755-2721(Print) / 2755-273X(Online)

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References

[1]. LIU Duan-yang. Design and implementation of video recommendation system based on deep viewing interest network. China Academic Journal Electric Publishing House, 2021.6.1, 18,19

[2]. LIU Xian-feng, LIU Tong-cun. Research on project grading prediction and recommendation algorithm based on attribute clustering, 2021,9,10,11

[3]. SU Kai, ZHANG Xuan, FU jin. Collaborative filtering algorithm based on attribute clustering and similarity optimization. China Academic Journal Electric Publishing House, 2021,11,30, 3,4

[4]. SUN Hong-mei. Research on Optimization of Collaborative Filtering. Algorithm.China Academic Journal Electric Publishing House,2021.5.1,1

[5]. WEN Feng-ming, XIE Fang-xue, Operational logic and ethical concerns of short video recommendation algorithms,China Academic Journal Electric Publishing House,2021.8.6,2

[6]. GU Ming-xing, Huang Wei-jian, Huang yuan.Collaborative filtering recommendation combining attribute clustering and improving user similarity,2020, 187,188,189

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