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Conversational ontology operator: patient-centric vaccine dialogue management engine for spoken conversational agents

BACKGROUND: Previously, we introduced our Patient Health Information Dialogue Ontology (PHIDO) that manages the dialogue and contextual information of the session between an agent and a health consumer. In this study, we take the next step and introduce the Conversational Ontology Operator (COO), th...

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Detalles Bibliográficos
Autores principales: Amith, Muhammad, Lin, Rebecca Z., Cui, Licong, Wang, Dennis, Zhu, Anna, Xiong, Grace, Xu, Hua, Roberts, Kirk, Tao, Cui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734717/
https://www.ncbi.nlm.nih.gov/pubmed/33317519
http://dx.doi.org/10.1186/s12911-020-01267-y
Descripción
Sumario:BACKGROUND: Previously, we introduced our Patient Health Information Dialogue Ontology (PHIDO) that manages the dialogue and contextual information of the session between an agent and a health consumer. In this study, we take the next step and introduce the Conversational Ontology Operator (COO), the software engine harnessing PHIDO. We also developed a question-answering subsystem called Frankenstein Ontology Question-Answering for User-centric Systems (FOQUS) to support the dialogue interaction. METHODS: We tested both the dialogue engine and the question-answering system using application-based competency questions and questions furnished from our previous Wizard of OZ simulation trials. RESULTS: Our results revealed that the dialogue engine is able to perform the core tasks of communicating health information and conversational flow. Inter-rater agreement and accuracy scores among four reviewers indicated perceived, acceptable responses to the questions asked by participants from the simulation studies, yet the composition of the responses was deemed mediocre by our evaluators. CONCLUSIONS: Overall, we present some preliminary evidence of a functioning ontology-based system to manage dialogue and consumer questions. Future plans for this work will involve deploying this system in a speech-enabled agent to assess its usage with potential health consumer users.