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Mining and Construction of User Experience Content: An Approach of Feature Analysis Based on Image

  • Di WangEmail author
  • Nan Liang
  • Jiaming Zhong
  • Liqun Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9748)

Abstract

This research is a preliminary study for a professional museum of print ads during the period of Republic of China. We selected 571 pieces of print ads of the Republic of China as sample to analysis the feature of them to make the visitors of museum could more immersive feel the print ads of the Republic of China and experience the unique charm of imagery modeling and visual language. The main methods used in the research are image feature analysis and image feature quantization calculation, we extract and summarize the common elements and culture style feature based on the analysis of multidimensional design elements. The research results could provide effective guidance for the design of the professional museum, including the overall atmosphere of the museum, thematic construction and situation creation.

Keywords

Image analysis Feature quantification Multidimensional scaling analysis Correspondence analysis 

References

  1. 1.
    Xie, H., Li, Q., Mao, X., et al.: Mining latent user community for tag-based and content-based search in social media. Comput. J. 57(9), 1415–1430 (2014)CrossRefGoogle Scholar
  2. 2.
    He, W.: Improving user experience with case-based reasoning systems using text mining and Web 2.0. Exp. Syst. Appl. 40(2), 500–507 (2013)CrossRefGoogle Scholar
  3. 3.
    Moscato, V., Picariello, A., Rinaldi, A.M.: Towards a user based recommendation strategy for digital ecosystems. Knowl. Based Syst. 37, 165–175 (2013)CrossRefGoogle Scholar
  4. 4.
    Qi, G.J., Aggarwal, C., Tian, Q., et al.: Exploring context and content links in social media: a latent space method. IEEE Trans. Pattern Anal. Mach. Intell. 34(5), 850–862 (2012)CrossRefGoogle Scholar
  5. 5.
    Shim, H., Lee, S.: Multi-channel electromyography pattern classification using deep belief networks for enhanced user experience. J. Cent. S. Univ. 22(5), 1801–1808 (2015)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Martins, D.S., Oliveira, L.S., Pimentel, M.G.C.: Designing the user experience in iTV-based interactive learning objects. In: Proceedings of the 28th ACM International Conference on Design of Communication, pp. 243–250. ACM (2010)Google Scholar
  7. 7.
    Lei, T., Liu, X., Wu, L., Chen, T., Wang, Y., Xiong, L., Wei, S.: The impact of natural utilization of traditional Chinese cultural elements on the user experience in mobile interaction design. In: Rau, P. (ed.) CCD 2015. LNCS, vol. 9181, pp. 46–56. Springer, Heidelberg (2015)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Di Wang
    • 1
    Email author
  • Nan Liang
    • 1
  • Jiaming Zhong
    • 1
  • Liqun Zhang
    • 1
  1. 1.Design Management InstituteShanghai Jiao Tong UniversityShanghaiChina

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