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Thread Reconstruction in Conversational Data using Neural Coherence Models

T. Nguyen,Shafiq R. Joty,Basma El Amel Boussaha,M. de Rijke

Published 2017 in arXiv.org

ABSTRACT

Discussion forums are an important source of information. They are often used to answer specific questions a user might have and to discover more about a topic of interest. Discussions in these forums may evolve in intricate ways, making it difficult for users to follow the flow of ideas. We propose a novel approach for automatically identifying the underlying thread structure of a forum discussion. Our approach is based on a neural model that computes coherence scores of possible reconstructions and then selects the highest scoring, i.e., the most coherent one. Preliminary experiments demonstrate promising results outperforming a number of strong baseline methods.

PUBLICATION RECORD

  • Publication year

    2017

  • Venue

    arXiv.org

  • Publication date

    2017-07-24

  • Fields of study

    Computer Science

  • Identifiers
    arXiv 1707.07660
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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  • No concepts are published for this paper.

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