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Improving the Quality of Art Market Data Using Linked Open Data and Machine Learning

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Business Information Systems Workshops (BIS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 263))

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Abstract

Among numerous research studies devoted to art markets, very little attention is given to the quality of the data. Availability of a decent amount of observations is a problem in many fields; the art market is no different, especially in Poland. Therefore, it constitutes a severe obstacle in explaining the market behaviour. The use of Linked Open Data and Machine Learning can pave the way to improve the quality of data and enrich results of other art market research as a consequence, such as building indices. This paper is an outline of the method for combining such fields and summarises effort already made to achieve that.

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Notes

  1. 1.

    http://deepart.io.

  2. 2.

    http://nutch.apache.org.

  3. 3.

    http://scrapy.org.

  4. 4.

    https://tika.apache.org.

  5. 5.

    http://www.wikiart.org.

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Authors and Affiliations

  1. Departament of Information Systems, Poznań University of Economics and Business, Aleja Niepodległości 10, Poznań, Poland

    Dominik Filipiak & Agata Filipowska

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  1. Dominik Filipiak
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  2. Agata Filipowska
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Correspondence to Dominik Filipiak .

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Editors and Affiliations

  1. Poznań University of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. Leipzig University, Leipzig, Germany

    Rainer Alt

  3. Leipzig University, Leipzig, Germany

    Bogdan Franczyk

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Filipiak, D., Filipowska, A. (2017). Improving the Quality of Art Market Data Using Linked Open Data and Machine Learning. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems Workshops. BIS 2016. Lecture Notes in Business Information Processing, vol 263. Springer, Cham. https://doi.org/10.1007/978-3-319-52464-1_39

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