Research on the Innovation of Talent Training in Fashion Performance Under the Background of Big Data
- DOI
- 10.2991/978-94-6463-172-2_15How to use a DOI?
- Keywords
- Big Data; New Media; Fashion performance; Talent Training; Innovation
- Abstract
With the continuous development of current society, the development trend of network, data and information has been presented, which provides a good opportunity for the development of new media technology in the fashion industry. The emergence of new media provides a carrier for the presentation of Internet big data, which can better provide accurate services for the fashion industry. The application of Internet big data provides impetus for the development of new media in the fashion industry. Based on this, the author expounds the characteristics of talent training for fashion performance, analyzes the beneficial influence of Internet big data and new media technology on the integration of fashion industry, and finally puts forward the concrete practical path to promote the integration of new media technology and talent training for fashion performance in the era of big data.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qianwen Li AU - Min Yin PY - 2023 DA - 2023/06/30 TI - Research on the Innovation of Talent Training in Fashion Performance Under the Background of Big Data BT - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023) PB - Atlantis Press SP - 125 EP - 131 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-172-2_15 DO - 10.2991/978-94-6463-172-2_15 ID - Li2023 ER -