Abstract
High complexity of business processes is a continually growing problem in real-life organisations. Hence, modelling a workflow poses a challenge for different participants. Many methods have been proposed for automatic generation of process models. This paper aims at presenting an approach for uniting knowledge from a number of stakeholders. In essence, a collection of tabular tasks definitions are combined into one classification of unordered activities. Later, semantic analysis of the input definitions is suggested in order to fuse them based on similarity of parameters. Using a set of predefined constraints and a dedicated construction algorithm, the resulting spreadsheet-based structure can then be converted into a model of a process.
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The Natural Language Toolkit, see https://www.nltk.org/.
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Kluza, K. et al. (2021). Using a Semantic-Based Support System for Merging Knowledge from Process Participants. In: Owoc, M.L., Pondel, M. (eds) Artificial Intelligence for Knowledge Management. AI4KM 2019. IFIP Advances in Information and Communication Technology, vol 599. Springer, Cham. https://doi.org/10.1007/978-3-030-85001-2_1
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