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Communication Dans Un Congrès Année : 2017

Thread Reconstruction in Conversational Data using Neural Coherence

Résumé

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.
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Dates et versions

hal-01741457 , version 1 (23-03-2018)

Identifiants

  • HAL Id : hal-01741457 , version 1

Citer

Dat Tien Nguyen, Shafiq Joty, Basma El Amel Boussaha, Maarten de Rijke. Thread Reconstruction in Conversational Data using Neural Coherence. Neu-IR: Workshop on Neural Information Retrieval, Aug 2017, Tokyo, Japan. ⟨hal-01741457⟩
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