Visible to the public Flexible Modelling using Conversational Agents

TitleFlexible Modelling using Conversational Agents
Publication TypeConference Paper
Year of Publication2019
AuthorsPérez-Soler, Sara, Guerra, Esther, de Lara, Juan
Conference Name2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)
Date PublishedSeptember 2019
PublisherIEEE
ISBN Number978-1-7281-5125-0
Keywordschatbots, conversational agent, conversational agents, conversational modelling framework, domain-specific modelling, flexible modelling, Human Behavior, meta-model relaxation, Metrics, natural language processing, pubcrawl, Scalability, social network, social networking (online), social networks, software agents, software engineering, software engineering tasks, software services
Abstract

The advances in natural language processing and the wide use of social networks have boosted the proliferation of chatbots. These are software services typically embedded within a social network, and which can be addressed using conversation through natural language. Many chatbots exist with different purposes, e.g., to book all kind of services, to automate software engineering tasks, or for customer support. In previous work, we proposed the use of chatbots for domain-specific modelling within social networks. In this short paper, we report on the needs for flexible modelling required by modelling using conversation. In particular, we propose a process of meta-model relaxation to make modelling more flexible, followed by correction steps to make the model conforming to its meta-model. The paper shows how this process is integrated within our conversational modelling framework, and illustrates the approach with an example.

URLhttps://ieeexplore.ieee.org/document/8904633
DOI10.1109/MODELS-C.2019.00076
Citation Keyperez-soler_flexible_2019