Can We Build Recommender System for Artwork Evaluation?

Cezary Pawłowski , Anna Gelich , Zbigniew W. Raś

Abstract

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.
Author Cezary Pawłowski (FEIT / ICS)
Cezary Pawłowski,,
- The Institute of Computer Science
, Anna Gelich
Anna Gelich,,
-
, Zbigniew W. Raś (FEIT / IN)
Zbigniew W. Raś,,
- The Institute of Computer Science
Pages41-52
Publication size in sheets0.55
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 EnglishData Mining, Recommender Systems, Art Market, Paintings
DOIDOI:10.1007/978-3-319-77604-0_4
URL https://www.springer.com/la/book/9783319776033
Languageen angielski
File
20170037.pdf 733.33 KB
Score (nominal)20
Score sourcepublisherList
ScoreMinisterial score = 20.0, 20-10-2019, ChapterFromConference
Citation count*1 (2019-08-04)
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