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Quantitative Analysis of Art Market Using Ontologies, Named Entity Recognition and Machine Learning: A Case Study

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Business Information Systems (BIS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 255))

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Abstract

In the paper we investigate new approaches to quantitative art market research, such as statistical analysis and building of market indices. An ontology has been designed to describe art market data in a unified way. To ensure the quality of information in the knowledge base of the ontology, data enrichment techniques such as named entity recognition (NER) or data linking are also involved. By using techniques from computer vision and machine learning, we predict a style of a painting. This paper comes with a case study example being a detailed validation of our approach.

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Notes

  1. 1.

    http://www.artasanasset.com.

  2. 2.

    Due to the problem of overfitting.

  3. 3.

    WikiArt.org – Encyclopedia of fine arts, http://www.wikiart.org.

  4. 4.

    http://christies.com/lotfinder/paintings/claude-monet-le-parlement-soleil-couchant-5895978-details.aspx.

  5. 5.

    http://dbpedia.org/resource/Claude_Monet.

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Author information

Authors and Affiliations

  1. Department of Information Systems, Poznań University of Economics, Al. Niepodległości 10, 61-875, Poznań, Poland

    Dominik Filipiak & Agata Filipowska

  2. Hasso-Plattner-Institut, Prof.-Dr.-Helmert-Straße 2-3, 14482, Potsdam, Germany

    Henning Agt-Rickauer, Christian Hentschel & Harald Sack

Authors
  1. Dominik Filipiak
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  2. Henning Agt-Rickauer
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  3. Christian Hentschel
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  4. Agata Filipowska
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  5. Harald Sack
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Corresponding author

Correspondence to Dominik Filipiak .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Poznan Univ of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. Institut für Wirtschaftsinformatik, Universität Leipzig, Leipzig, Sachsen, Germany

    Rainer Alt

  3. Information System Institute, University of Leipzig, Leipzig, Germany

    Bogdan Franczyk

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Filipiak, D., Agt-Rickauer, H., Hentschel, C., Filipowska, A., Sack, H. (2016). Quantitative Analysis of Art Market Using Ontologies, Named Entity Recognition and Machine Learning: A Case Study. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems. BIS 2016. Lecture Notes in Business Information Processing, vol 255. Springer, Cham. https://doi.org/10.1007/978-3-319-39426-8_7

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