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  • 标题:Classification and Visual Design Analysis of Network Expression Based on Big Data Multimodal Intelligence Technology
  • 本地全文:下载
  • 作者:Zou Ping ; Yueyan Liu
  • 期刊名称:Discrete Dynamics in Nature and Society
  • 印刷版ISSN:1026-0226
  • 电子版ISSN:1607-887X
  • 出版年度:2022
  • 卷号:2022
  • DOI:10.1155/2022/7542606
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:The rapid development of the Internet in modern society has promoted the development of many different network platforms. In the context of big data, many types of multimodal data such as pictures, videos, and texts are generated in the platform. Through the analysis of multimodal data, we can provide better services for users. The traditional big data analysis platform cannot achieve a completely stable state for the analysis of multimodal data. The construction of multimodal intelligent platform can achieve efficient analysis of relevant data, so as to create greater economic benefits for the society. This paper mainly studies the historical development trend of big data multimodal intelligence technology and the data processing method of multimodal intelligence technology applied to network expression classification, including data acquisition, storage, and analysis. Finally, it studied the fusion algorithm between multimodal data and visual design, as well as the classification of network expression and the application result analysis of visual design in big data multimodal intelligence technology.
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