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Basic Level Concepts as a Means to Better Interpretability of Boolean Matrix Factors and Their Application to Clustering

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Modeling Decisions for Artificial Intelligence (MDAI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11144))

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Abstract

We present an initial study linking in cognitive psychology well known phenomenon of basic level concepts and a general Boolean matrix factorization method. The result of this fusion is a new algorithm producing factors that explain a large portion of the input data and that are easy to interpret. Moreover, the link with the cognitive psychology allowed us to design a new clustering algorithm that groups objects into clusters that are close to human perception. In addition we present experiments that provide insight to the relationship between basic level concepts and Boolean factors.

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Notes

  1. 1.

    In [6] this algorithm is named Algorithm 1.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Palacky University Olomouc, 17. listopadu 12, 77146, Olomouc, Czech Republic

    Petr Krajča & Martin Trnecka

Authors
  1. Petr Krajča
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  2. Martin Trnecka
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Corresponding author

Correspondence to Petr Krajča .

Editor information

Editors and Affiliations

  1. Maynooth University, Maynooth, Ireland

    Vicenç Torra

  2. Department Management Science, Tamagawa University, Tokyo, Japan

    Yasuo Narukawa

  3. University of the Balearic Islands, Palma de Mallorca, Spain

    Isabel Aguiló

  4. University of the Balearic Islands, Palma de Mallorca, Baleares, Spain

    Manuel González-Hidalgo

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Krajča, P., Trnecka, M. (2018). Basic Level Concepts as a Means to Better Interpretability of Boolean Matrix Factors and Their Application to Clustering. In: Torra, V., Narukawa, Y., Aguiló, I., González-Hidalgo, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2018. Lecture Notes in Computer Science(), vol 11144. Springer, Cham. https://doi.org/10.1007/978-3-030-00202-2_14

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  • DOI: https://doi.org/10.1007/978-3-030-00202-2_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00201-5

  • Online ISBN: 978-3-030-00202-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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