Finite State Machines in the Context of Knowledge Based Transformations (Invited)

Schick, Johannes; Wagner, Marc; Lippe, Wolfram-Manfred

Forschungsartikel in Sammelband (Konferenz) | Peer reviewed

Zusammenfassung

In this paper we apply a novel approach for transforming models between textual and graphical representations using knowledge graphs within the sphere of meta-modeling and model transformations. We will use an example involving a finite state machine (FSM). FSMs are basic components in many modeling languages. Unlike traditional transformation methods, our technique uniquely addresses the limitations in transforming complex models between modalities, specifically textual and graphical representations. This approach has significant implications for the development of advanced AI-driven multimodal transformation tools and knowledge graphs, providing a robust framework for future research and practical applications in various domains.

Details zur Publikation

Herausgeber*innenIEEE Computer Society, or the Institute of Electrical and Electronics Engineers, Inc.
BuchtitelProceedings of the International Conference on AI x Business (AIxB 2025)
Seitenbereich72-76
VerlagWiley-IEEE Computer Society Press
ErscheinungsortPiscataway, NJ
StatusVeröffentlicht
Veröffentlichungsjahr2025 (05.05.2026)
Sprache, in der die Publikation verfasst istEnglisch
KonferenzInternational Conference on AI x Business (AIxB 2025), 1-3 Oktober 2025, Laguna Hills, CA, Vereinigte Staaten
ISBN979-8-3315-7126-9;979-8-3315-7127-6
StichwörterModeling; System analysis and design; Semantics; Software engineering; Knowledge graphs; AI transformation

Autor*innen der Universität Münster

Lippe, Wolfram-Manfred