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Probabilistic Topic Modeling of the Russian Text Corpus on Musicology

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Language, Music, and Computing (LMAC 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 561))

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Abstract

The paper describes the results of experiments on the development of a statistical model of the Russian text corpus on musicology. We construct a topic model based on Latent Dirichlet Allocation and process corpus data with the help of the GenSim statistical toolkit. Results achieved in course of experiments allow us to distinguish general and special topics which describe conceptual structure of the corpus in question and to analyze paradigmatic and syntagmatic relations between lemmata within topics.

The research discussed in the paper is supported by the grant of St.-Petersburg State University № 30.38.305.2014 «Quantitative linguistic parameters for defining stylistic characteristics and subject area of texts».

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Authors and Affiliations

  1. Faculty of Philology, Department of Mathematical Linguistics, Saint Petersburg State University, Universitetskaya embankment, Saint Petersburg, 199034, Russia

    Olga Mitrofanova

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  1. Olga Mitrofanova
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Correspondence to Olga Mitrofanova .

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Editors and Affiliations

  1. Saint Petersburg State University of Aerospace Instrumentation, St. Petersburg, Russia

    Polina Eismont

  2. University of Wolverhampton, Wolverhampton, United Kingdom

    Natalia Konstantinova

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Mitrofanova, O. (2015). Probabilistic Topic Modeling of the Russian Text Corpus on Musicology. In: Eismont, P., Konstantinova, N. (eds) Language, Music, and Computing. LMAC 2015. Communications in Computer and Information Science, vol 561. Springer, Cham. https://doi.org/10.1007/978-3-319-27498-0_6

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  • DOI: https://doi.org/10.1007/978-3-319-27498-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27497-3

  • Online ISBN: 978-3-319-27498-0

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