Graph-based representations of clarification strategies supporting automatic dialogue management
This paper aims at presenting a dialogue-oriented approach to the construction of a graph knowledge base (KB) supporting task-oriented human-machine interactions. In particular, we focus on different pragmatic scenarios, facing the Common Ground issue and arguing that knowledge bases (in the form of...
Enregistré dans:
| Dans: | URI:https://journals.openedition.org/ijcol, |
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| Auteurs principaux: | , , , |
| Format: | Article ou chapitre numérique |
| Langue: | Anglais |
| Publié: |
IJCoL
2022
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| Accès en ligne: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |
| Résumé: | This paper aims at presenting a dialogue-oriented approach to the construction of a graph knowledge base (KB) supporting task-oriented human-machine interactions. In particular, we focus on different pragmatic scenarios, facing the Common Ground issue and arguing that knowledge bases (in the form of graphs) are needed to make a clarification and recover pieces of information when inconsistencies occur during the communicative exchange.The main contributions of this work are: 1) a flexible dialog system architecture designed to be plugged into existing service infrastructures, 2) a graph-based knowledge representation protocol to manage both dialog domain and dialog management, 3) a detailed investigation of clarification requests forms with respect to their functions. After a brief introduction (see Section 1), we present: the theoretical underpinnings of the paper and the background work (see Section 2) our system architecture (see Sections 3 and 4) and the clarification requests (CRs) issue (see Section 5); our CRs classification, and some examples in context (see Section 6). |
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