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Towards Explaining the Spectrogram of Graph Spectral Clustering in Text Document Domain

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Computer Information Systems and Industrial Management (CISIM 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14902))

Abstract

In previous research, the authors found that the spectrogram of eigenvalues of combinatorial Laplacian of the document similarity matrix is relevant for tasks like graph spectral classification, clustering etc.. This paper investigates the hypothesis that this property can be attributed to the specific “style” of writing, that is to the distribution of words in the documents belonging to a given category of documents. The investigation is performed via generating artificial documents from a predefined parameterized word distribution. The document similarity matrices are computed and the spectrum of the corresponding combinatorial Laplacian is interrogated. The parameters are varied to determine their impact. We present the impact of these parameters on the shape of the spectrogram.

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Acknowledgments

This study was funded by Polish Ministry of Science.

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Authors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, ul.Jana Kazimierza 5, 01-238, Warsaw, Poland

    Mieczysław A. Kłopotek, Sławomir T. Wierzchoń, Bartłomiej Starosta, Dariusz Czerski & Piotr Borkowski

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  1. Mieczysław A. Kłopotek
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  2. Sławomir T. Wierzchoń
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  3. Bartłomiej Starosta
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  4. Dariusz Czerski
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  5. Piotr Borkowski
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Correspondence to Mieczysław A. Kłopotek .

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Editors and Affiliations

  1. Bialystok University of Technology, Białystok, Poland

    Khalid Saeed

  2. VSB - Technical University of Ostrava, Ostrava, Czech Republic

    Jiří Dvorský

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Kłopotek, M.A., Wierzchoń, S.T., Starosta, B., Czerski, D., Borkowski, P. (2024). Towards Explaining the Spectrogram of Graph Spectral Clustering in Text Document Domain. In: Saeed, K., Dvorský, J. (eds) Computer Information Systems and Industrial Management. CISIM 2024. Lecture Notes in Computer Science, vol 14902. Springer, Cham. https://doi.org/10.1007/978-3-031-71115-2_26

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  • DOI: https://doi.org/10.1007/978-3-031-71115-2_26

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