Montecchiari, Devid

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Montecchiari
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Devid
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Devid Montecchiari

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Attachments: Yes × Start date: 2020 × End date: 2021 ×

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Now showing 1 - 2 of 2
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    Publication
    Ontology-based validation of enterprise architecture principles in enterprise models
    (2021) Montecchiari, Devid [in: Joint Proceedings of the BIR 2021 Workshops and Doctoral Consortium co-located with 20th International Conference on Perspectives in Business Informatics Research (BIR 2021)]
    Enterprises use Enterprise Architecture Principles as a guiding set of rules to provide a basis for decision making. These principles are described using natural language and are not machine-interpretable. The validation of these principles in models is a complex and time-consuming task. The goal of this research is to help humans in this review. Annotating enterprise architecture models with an enterprise ontology and representing architecture principles as rules, it is possible to automatically check architecture principles. The proposed approach is to combine both the domain knowledge and the modeling language knowledge to reason about models, allowing the automatic check of architecture principles.
    04B - Beitrag Konferenzschrift
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    Publication
    Hybrid conversational AI for intelligent tutoring systems
    (Sun SITE, Informatik V, RWTH Aachen, 2021) Pande, Charuta; Witschel, Hans Friedrich; Martin, Andreas; Montecchiari, Devid; Martin, Andreas; Hinkelmann, Knut; Fill, Hans-Georg; Gerber, Aurona; Lenat, Dough; Stolle, Reinhard; Harmelen, Frank van [in: Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021)]
    We present an approach to improve individual and self-regulated learning in group assignments. We focus on supporting individual reflection by providing feedback through a conversational system. Our approach leverages machine learning techniques to recognize concepts in student utterances and combines them with knowledge representation to infer the student’s understanding of an assignment’s cognitive requirements. The conversational agent conducts end-to-end conversations with the students and prompts them to reflect and improve their understanding of an assignment. The conversational agent not only triggers reflection but also encourages explanations for partial solutions.
    04B - Beitrag Konferenzschrift