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Reusable Abstractions and Patterns for Recognising compositional conversational flows

Sara Bouguelia 1, 2, 3 Hayet Brabra 1, 2 Shayan Zamanirad 4 Boualem Benatallah 4, 1, 2 Marcos Baez 1, 2 Hamamache Kheddouci 1, 3 
2 BD - Base de Données
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
3 GOAL - Graphes, AlgOrithmes et AppLications
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Task-oriented conversational bots allow users to access services and perform tasks through natural language conversations. However, integrating these bots and software-enabled services has not kept pace with our ability to deploy individual devices and services. The main drawbacks of current bots and services integration techniques stem from the inherent development and maintenance cost. In addition, existing Natural Language Processing (NLP) techniques automate various tasks but the synthesis of API calls to support broad range of potentially complex user intents is still largely a manual and costly process. In this paper, we propose three types of reusable patterns for recognising compositional conversational flows and therefore automatically support increased complexity and expressivity during the conversation.
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https://hal.archives-ouvertes.fr/hal-03295582
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Submitted on : Thursday, July 22, 2021 - 11:22:37 AM
Last modification on : Thursday, March 31, 2022 - 2:53:01 PM
Long-term archiving on: : Saturday, October 23, 2021 - 6:18:44 PM

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Sara Bouguelia, Hayet Brabra, Shayan Zamanirad, Boualem Benatallah, Marcos Baez, et al.. Reusable Abstractions and Patterns for Recognising compositional conversational flows. Advanced Information Systems Engineering - 33rd International Conference, CAiSE 2021, Jun 2021, Melbourne (on line), Australia. ⟨10.1007/978-3-030-79382-1_10⟩. ⟨hal-03295582⟩

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