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Sharing process models on the web has emerged as a common practice. Users cancollect and share their experimental process models with others. However, someusers always feel confused about the shared process models for lack ofnecessary guidelines or instructions. Therefore, several process translatorshave been proposed to explain the semantics of process models in naturallanguage (NL). We find that previous studies suffer from information loss andgenerate semantically erroneous descriptions that diverge from original modelbehaviors. In this paper, we propose a novel process translator named BePT(Behavior-based Process Translator) based on the encoder-decoder paradigm,encoding a process model into a middle representation and decoding therepresentation into NL descriptions. Our theoretical analysis demonstrates thatBePT satisfies behavior correctness, behavior completeness and descriptionminimality. The qualitative and quantitative experiments show that BePToutperforms the state-of-the-art baselines.

BePT: A Behavior-based Process Translator for Interpreting and Understanding Process Models