Can We Build Recommender System for Artwork Evaluation?
Cezary Pawłowski , Anna Gelich , Zbigniew W. Raś
AbstractThe 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.
|Publication size in sheets||0.55|
|Book||Bembenik Robert, Skonieczny Łukasz, Protaziuk Grzegorz M., Kryszkiewicz Marzena, Rybiński Henryk (eds.): Intelligent Methods and Big Data in Industrial Applications, Studies in Big Data, vol. 40, 2019, Springer International Publishing, ISBN 978-3-319-77603-3, [978-3-319-77604-0], 376 p., DOI:10.1007/978-3-319-77604-0|
|Keywords in English||Data Mining, Recommender Systems, Art Market, Paintings|
|Score|| = 15.0, 03-04-2019, BookChapterSeriesAndMatConf|
= 15.0, 03-04-2019, BookChapterSeriesAndMatConf
|Citation count*||1 (2019-08-04)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.