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        <title>Ontology Population Reusing Resources for Dialogue Intent Detection: Generic and Multilingual Approach</title>
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    <abstract>This work presents a generic semi-automatic strategy to populate the domain ontology of an ontology-driven task-oriented dialogue system, with the aim of performing successful intent detection in the dialogue process, reusing already existing multilingual resources. This semi-automatic approach allows ontology engineers to exploit available resources so as to associate the potential situations in the use case to FrameNet frames and obtain the relevant lexical units associated to them in the target language, following lexical and semantic criteria, without linguistic expert knowledge. This strategy has been validated and evaluated in two use cases, from industrial scenarios, for interaction in Spanish with a guide robot and with a Computerized Maintenance Management System (CMMS). In both cases, this method has allowed the ontology engineer to instantiate the domain ontology with the intent-relevant information with quality data in a simple and low-resource-consuming manner.</abstract>
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%0 Conference Proceedings
%T Ontology Population Reusing Resources for Dialogue Intent Detection: Generic and Multilingual Approach
%A Aceta, Cristina
%A Fernández, Izaskun
%A Soroa, Aitor
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
%D 2021
%8 September
%I INCOMA Ltd.
%C Held Online
%F aceta-etal-2021-ontology
%X This work presents a generic semi-automatic strategy to populate the domain ontology of an ontology-driven task-oriented dialogue system, with the aim of performing successful intent detection in the dialogue process, reusing already existing multilingual resources. This semi-automatic approach allows ontology engineers to exploit available resources so as to associate the potential situations in the use case to FrameNet frames and obtain the relevant lexical units associated to them in the target language, following lexical and semantic criteria, without linguistic expert knowledge. This strategy has been validated and evaluated in two use cases, from industrial scenarios, for interaction in Spanish with a guide robot and with a Computerized Maintenance Management System (CMMS). In both cases, this method has allowed the ontology engineer to instantiate the domain ontology with the intent-relevant information with quality data in a simple and low-resource-consuming manner.
%U https://aclanthology.org/2021.ranlp-1.2
%P 10-18

Markdown (Informal)

[Ontology Population Reusing Resources for Dialogue Intent Detection: Generic and Multilingual Approach](https://aclanthology.org/2021.ranlp-1.2) (Aceta et al., RANLP 2021)

• Ontology Population Reusing Resources for Dialogue Intent Detection: Generic and Multilingual Approach (Aceta et al., RANLP 2021)

ACL

• Cristina Aceta, Izaskun Fernández, and Aitor Soroa. 2021. Ontology Population Reusing Resources for Dialogue Intent Detection: Generic and Multilingual Approach. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 10–18, Held Online. INCOMA Ltd..