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Business processes are captured by models that serve as a basis for communication and training purposes, but this modeling is still a time consuming manual job. Semantic annotation of process models in combination with AI planning approaches can contribute to solve this drawback enabling an automatic creation of process models. But the semantic annotated process fragments necessary for starting the planning are often missing at all or not up-to-date anymore. Therefore, this work describes an approach for the semantic annotation and semantic-based planning of process models and introduces Cystid, an integration of Process Mining algorithms and semantic-based planning.
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Stored only when both papers are in the corpus — 13 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.