Can We Build Recommender System for Artwork Evaluation?

  • Cezary Pawlowski
  • Anna Gelich
  • Zbigniew W. Raś
Part of the Studies in Big Data book series (SBD, volume 40)


The aim of this paper is to propose a strategy of building recommender system for assigning a price tag to an artwork. The other goal is to verify a hypothesis about existence of a co-relation between certain attributes used to describe a painting and its price. The paper examines the possibility of using methods of data mining in the field of art marketing. It also describes the main aspects of system architecture and performed data mining experiments as well as processes connected with data collection from the World Wide Web.


Data mining Recommender systems Art market Paintings 


  1. 1.
    Ricci, F., Rokach, L., Shapira, B., Kantor, P.B.: Recommender Systems Handbook, 1st edn. Springer, New York (2010)zbMATHGoogle Scholar
  2. 2.
    Kuang, J., Daniel, A., Johnston, J., Ras, Z.: Hierarchically structured recommender system for improving NPS of a company. LNCS, vol. 8536. Springer (2014)Google Scholar
  3. 3.
    SaatchiArt, Home page.
  4. 4.
    Artfinder, Home page.
  5. 5.
    UGallery, Home page.
  6. 6.
    DeviantArt, Home page.
  7. 7.
  8. 8.
  9. 9.
    Sharma, G., Wu, W., Dalal, E.N.: The CIEDE2000 color-difference formula: implementation notes, supplementary test data, and mathematical observations, Color Res. Appl. 30(1):2130 (2005)CrossRefGoogle Scholar
  10. 10.
    Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679–698 (1986)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Cezary Pawlowski
    • 1
  • Anna Gelich
    • 2
  • Zbigniew W. Raś
    • 1
    • 2
    • 3
  1. 1.Institute of Computer Science, Warsaw University of TechnologyWarsawPoland
  2. 2.Department of Computer ScienceUniversity of North CarolinaCharlotteUSA
  3. 3.Polish-Japanese Academy of Information TechnologyWarsawPoland

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