Communication Dans Un Congrès Année : 2021

Gathering Information and Engaging the User ComBot : A Task-Based, Serendipitous Dialog Model for Patient-Doctor Interactions

Résumé

We focus on dialog models in the context of clinical studies where the goal is to help gather, in addition to the closed set of information collected based on a questionnaire, serendipitous information that is medically relevant. To promote user engagement and address this dual goal (collecting both a predefined set of data points and more informal information about the state of the patients), we introduce an ensemble model made of three bots: a task-based, a follow-up and a social bot. We introduce a generic method for developing follow-up bots. We compare different ensemble configurations and we show that the combination of the three bots (i) provides a better basis for collecting information than just the information seeking bot and (ii) collects information in a more efficient manner that an ensemble model combining the information seeking and the social bot.

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Cite 10.18653/v1/2021.nlpmc-1.3 Autre Liednikova, A., Jolivet, P., Durand-Salmon, A., & Gardent, C. (2021). Gathering Information and Engaging the User ComBot: A Task-Based, Serendipitous Dialog Model for Patient-Doctor Interactions. In Proceedings of the Second Workshop on Natural Language Processing for Medical Conversations (pp. 21–29). Proceedings of the Second Workshop on Natural Language Processing for Medical Conversations. Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.nlpmc-1.3

Dates et versions

hal-03461330 , version 1 (01-12-2021)

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  • HAL Id : hal-03461330 , version 1

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Anna Liednikova, Philippe Jolivet, Alexandre Durand-Salmon, Claire Gardent. Gathering Information and Engaging the User ComBot : A Task-Based, Serendipitous Dialog Model for Patient-Doctor Interactions. NLPMC 2021 - Second Workshop on Natural Language Processing for Medical Conversations, Jun 2021, Mexico, Mexico. pp.21-29. ⟨hal-03461330⟩
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