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Management and Optimization Methods of Music Audio-Visual Archives Resources Based on Big Data

Author

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  • Hongyu Liu

    (Henan Vocational College of Information and Statistics, China)

  • Chenxi Lu

    (North University of China, China)

Abstract

Protecting Oroqen folk songs is not only the only way to reproduce Chinese traditional music culture, but also the only way to rebuild its national spirit and enhance national cultural confidence. In view of the modernity problems of Oroqen folk songs in the current process of inheritance and protection, this paper puts forward the management and optimization methods of music audio-visual archives resources under the background of big data. This paper analyzes and discusses the resource management path of folk music audio-visual archives in Oroqen in the era of big data and designs a set of perfect digital music audio-visual archives resource management platform, which can not only facilitate the collection, storage, management, and utilization of paper files and electronic files in archives, but also optimize the retrieval algorithm of archives. The resource allocation algorithm based on Nash equilibrium solution is used to optimize it. The simulation results show that the proposed method reduces the information resource allocation time and improves the demand satisfaction.

Suggested Citation

  • Hongyu Liu & Chenxi Lu, 2023. "Management and Optimization Methods of Music Audio-Visual Archives Resources Based on Big Data," International Journal of Ambient Computing and Intelligence (IJACI), IGI Global, vol. 14(1), pages 1-15, January.
  • Handle: RePEc:igg:jaci00:v:14:y:2023:i:1:p:1-15
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