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Art Innovative Systems for Value Tagging

Art Innovative Systems for Value Tagging
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Author(s): Laurel Powell (University of North Carolina at Charlotte, USA), Anna Gelich (University of North Carolina at Charlotte, USA)and Zbigniew W. Ras (University of North Carolina at Charlotte, USA)
Copyright: 2021
Pages: 12
Source title: Encyclopedia of Organizational Knowledge, Administration, and Technology
Source Author(s)/Editor(s): Mehdi Khosrow-Pour D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-7998-3473-1.ch080

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Abstract

Prices of artworks are rather arbitrary. Artists use word of mouth and galleries to learn about pricing. Also, the professionals in the art market are searching the internet for information about prices of comparable artworks to the ones they plan to sell, but it is not very helpful. Existing systems do not use data analytics but human experts to evaluate fine art pieces and make recommendations. The system discussed in this article, called ArtIST, is based on big data analytics. Using the artist's name, appraisal of the piece of art is done by a personalized recommender system built from the data describing similar artists and similar art pieces including information about their sales. To evaluate an art piece using ArtIST, the user needs to submit the same information about the work as is required by existing art appraisal tools or websites.

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