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Performing and Visualizing Temporal Analysis of Large Text Data Issued for Open Sources: Past and Future Methods

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Book cover Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery (BDAS 2015, BDAS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 613))

Abstract

In this paper we first propose a state of the art on the methods for the visualization and for the interpretation of textual data, and in particular of scientific data. We then shortly present our contributions to this field in the form of original methods for the automatic classification of documents and easy interpretation of their content through characteristic keywords and classes created by our algorithms. In a second step, we focus our analysis on the data evolving over time. We detail our diachronic approach, especially suitable for the detection and for visualization of topic changes. This allows us to conclude with Diachronic’Explorer, our upcoming visualization tool for visual exploration of evolutionary data.

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Notes

  1. 1.

    See URL: http://cordis.europa.eu/fp7/ict/programme/fet_en.html.

  2. 2.

    The choice of the weighting scheme is not really constrained by the approach instead of producing positive values. Such scheme is supposed to figure out the significance (i.e. semantic and importance) of the feature for the data. Feature Recall is a scale independent measure but feature Predominance is not. We have however shown experimentally in (Lamirel et al., 2014a) that the F-measure which is a combination of these two measures is only weakly influenced by feature scaling. Nevertheless, to guaranty full scale independent behavior for this measure, data must be standardized.

  3. 3.

    The ISTEX project (Initiative d’Excellence pour l’Information Scientifique et Technique) fits in the “Investment for the future” program, initiated by the French Ministry of Higher Education and Research (MESR), whose ambition is to strengthen research and French higher education on the world level. The ISTEX project main objective is to offer to the whole of the community of higher education and research, online access to the retrospective collections of scientific literature in all disciplines by engaging a national policy of massive acquisition of documentation: archives of journals, databases, corpus of texts.

    Reference: http://www.istex.fr.

  4. 4.

    A demo version of the tool can be found at URL: http://github.com/nicolasdugue/istex-demonstrateur.

  5. 5.

    The principle of computation of the strength of a topic link between periods is explained with more details in [14].

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Authors and Affiliations

  1. Equipe Synalp, Bâtiment B, 54506, Vandoeuvre-lès-Nancy, France

    Jean-Charles Lamirel & Nicolas Dugué

  2. CNRS-Inist, Vandoeuvre-lès-Nancy, France

    Pascal Cuxac

Authors
  1. Jean-Charles Lamirel
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  2. Nicolas Dugué
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  3. Pascal Cuxac
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Corresponding author

Correspondence to Jean-Charles Lamirel .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

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Lamirel, JC., Dugué, N., Cuxac, P. (2016). Performing and Visualizing Temporal Analysis of Large Text Data Issued for Open Sources: Past and Future Methods. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_4

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  • DOI: https://doi.org/10.1007/978-3-319-34099-9_4

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