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A Method for Short Message Contextualization: Experiments at CLEF/INEX

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Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9283))

Abstract

This paper presents the approach we developed for automatic multi-document summarization applied to short message contextualization, in particular to tweet contextualization. The proposed method is based on named entity recognition, part-of-speech weighting and sentence quality measuring. In contrast to previous research, we introduced an algorithm from smoothing from the local context. Our approach exploits topic-comment structure of a text. Moreover, we developed a graph-based algorithm for sentence reordering. The method has been evaluated at INEX/CLEF tweet contextualization track. We provide the evaluation results over the 4 years of the track. The method was also adapted to snippet retrieval and query expansion. The evaluation results indicate good performance of the approach.

L. Ermakova—Ambassade de France en Russie, bourse de thèse en cotutelle.

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Authors and Affiliations

  1. Institut de Recherche en Informatique de Toulouse, Toulouse, France

    Liana Ermakova

  2. Perm State National Research University, Perm, Russia

    Liana Ermakova

Authors
  1. Liana Ermakova
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Correspondence to Liana Ermakova .

Editor information

Editors and Affiliations

  1. Institut de Recherche en Informatique de Toulouse, Toulouse , France

    Josanne Mothe

  2. Department of Computer Science, University of Neuchatel, Neuchâtel, Switzerland

    Jacques Savoy

  3. Faculteit der Geesteswetenschappen, Universiteit Amsterdam, Amsterdam, The Netherlands

    Jaap Kamps

  4. Institut de Recherche en Informatique de Toulouse, Toulouse, France

    Karen Pinel-Sauvagnat

  5. School of Computing, Dublin City University, Dublin, Ireland

    Gareth Jones

  6. LIA - CERI, Université d'Avignon et des Pays de Vaucluse, Avignon, France

    Eric San Juan

  7. Department of Information Engineering, University of Padua, Padua, Italy

    Linda Capellato

  8. of Information Engineering (DEI), University of Padua, Department, Padova, Italy

    Nicola Ferro

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Ermakova, L. (2015). A Method for Short Message Contextualization: Experiments at CLEF/INEX. In: Mothe, J., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2015. Lecture Notes in Computer Science(), vol 9283. Springer, Cham. https://doi.org/10.1007/978-3-319-24027-5_38

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  • DOI: https://doi.org/10.1007/978-3-319-24027-5_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24026-8

  • Online ISBN: 978-3-319-24027-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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