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Computer Science > Computation and Language

arXiv:2304.11065 (cs)
[Submitted on 19 Apr 2023 (v1), last revised 18 Jan 2024 (this version, v2)]

Title:Conversational Process Modeling: Can Generative AI Empower Domain Experts in Creating and Redesigning Process Models?

Authors:Nataliia Klievtsova, Janik-Vasily Benzin, Timotheus Kampik, Juergen Mangler, Stefanie Rinderle-Ma
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Abstract:AI-driven chatbots such as ChatGPT have caused a tremendous hype lately. For BPM applications, several applications for AI-driven chatbots have been identified to be promising to generate business value, including explanation of process mining outcomes and preparation of input data. However, a systematic analysis of chatbots for their support of conversational process modeling as a process-oriented capability is missing. This work aims at closing this gap by providing a systematic analysis of existing chatbots. Application scenarios are identified along the process life cycle. Then a systematic literature review on conversational process modeling is performed, resulting in a taxonomy of application scenarios for conversational process modeling, including paraphrasing and improvement of process descriptions. In addition, this work suggests and applies an evaluation method for the output of AI-driven chatbots with respect to completeness and correctness of the process models. This method consists of a set of KPIs on a test set, a set of prompts for task and control flow extraction, as well as a survey with users. Based on the literature and the evaluation, recommendations for the usage (practical implications) and further development (research directions) of conversational process modeling are derived.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2304.11065 [cs.CL]
  (or arXiv:2304.11065v2 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2304.11065

Submission history

From: Stefanie Rinderle-Ma [view email]
[v1] Wed, 19 Apr 2023 06:54:14 UTC (192 KB)
[v2] Thu, 18 Jan 2024 15:57:19 UTC (580 KB)
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