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Sun 10 - Sat 16 October 2021
Wed 13 Oct 2021 09:40 - 09:50 at Room 1 - Machine learning and Recommender systems I Chair(s): Betty H.C. Cheng

Domain modelling transforms informal requirements written in natural language in the form of problem descriptions into concise and analyzable domain models. As the manual construction of these domain models is often time-consuming, error-prone, and labor-intensive, several approaches already exist to automate domain modelling. However, the current approaches suffer from lower accuracy of extracted domain models and the lack of support for system-modeller interactions. To better assist modellers, we introduce DoMoBOT, a web-based Domain Modelling BOT. Our proposed bot combines artificial intelligence techniques such as natural language processing and machine learning to extract domain models with higher accuracy. More importantly, our bot incorporates a set of features to bring synergy between automated model extraction and bot-modeller interactions. During these interactions, the bot presents multiple possible solutions to a modeller for modelling scenarios present in a given problem description. The bot further enables modellers to switch to a particular solution and updates the other parts of the domain model proactively. In this tool demo paper, we demonstrate how the implementation and architecture of DoMoBOT support the paradigm of automated and interactive domain modelling for assisting modellers.

Wed 13 Oct

Displayed time zone: Osaka, Sapporo, Tokyo change

09:00 - 10:00
Machine learning and Recommender systems ITechnical Papers at Room 1
Chair(s): Betty H.C. Cheng Michigan State University
Using Recommender Systems to Improve Proactive ModelingJ1ST
Technical Papers
Predictions-on-Chip: Model-based Training and Automated Deployment of Machine Learning Models at RuntimeJ1ST
Technical Papers
Sebastian Pilarski McGill University, Martin Staniszewski , Matthew Bryan , Frederic Villeneuve , Daniel Varro McGill University / Budapest University of Technology and Economics
DoMoBOT: An AI-Empowered Bot for Automated and Interactive Domain ModellingDEMO
Technical Papers
Rijul Saini McGill University, Canada, Gunter Mussbacher McGill University, Jin L.C. Guo McGill University, Jörg Kienzle McGill University, Canada