Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 137-142.doi: 10.11896/jsjkx.210100017

• Big Data & Data Science • Previous Articles     Next Articles

Application Status and Future Trends of Photo Analysis in E-commerce:A Survey of Research Based on Photo Visual and Content Features

LIU Rong, ZHANG Ning   

  1. School of Business,Qingdao University,Qingdao,Shandong 266000,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:LIU Rong,born in 1996,postgraduate.Her main research interests include the application research on text mining and so on.
    ZHANG Ning,born in 1980,professor.His main research interests include business data analysis and user ceneratedcontent(UGC).
  • Supported by:
    Social Science Planning Project of Shandong Province,China(18CHLJ22) and Ethnic Research Projects of State Ethnic Affairs Commission in China(2018-GMB-022).

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Abstract: The development of computer deep learning and big data mining technology makes it possible to effectively extract the visual and content features of massive photos.Photo analysis has been widely used in e-commerce research.Through combing the related literatures of photo analysis,this paper reviews the methods and applications of photo feature extraction,puts forward an analysis framework based on the research and application of photo visual and content features,and systematically expounds the application status of photo analysis in the field of e-commerce.Through analysis,it is found that the existing related research mainly focuses on the influence of the visual or content features of photos on individual preference and consumption behavior.The effect of their combination remains to be further explored.And most of the research focuses on the general analysis of the photos posted by users on social networking sites,and lacks of further research on consumption behavior.Finally,it summarizes the future research and development direction of photo analysis in the field of e-commerce,which provides a certain reference for future research.

Key words: Deep learning, E-commerce, Photo analysis, Visual content analysis, Visual features

CLC Number: 

  • TP399
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