A
Artem Polyvyanyy
Researcher at University of Melbourne
Publications - 136
Citations - 2802
Artem Polyvyanyy is an academic researcher from University of Melbourne. The author has contributed to research in topics: Process modeling & Process mining. The author has an hindex of 28, co-authored 118 publications receiving 2234 citations. Previous affiliations of Artem Polyvyanyy include Queensland University of Technology & University of Potsdam.
Papers
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Book ChapterDOI
Simplified computation and generalization of the refined process structure tree
TL;DR: This paper provides two improvements to the Refined Process Structure Tree (RPST), and extends the applicability of the RPST to arbitrary directed graphs such that every node is on a path from some source to some sink.
Journal ArticleDOI
Split miner: automated discovery of accurate and simple business process models from event logs
Adriano Augusto,Adriano Augusto,Raffaele Conforti,Marlon Dumas,Marcello La Rosa,Artem Polyvyanyy +5 more
TL;DR: Split Miner as discussed by the authors combines a novel approach to filter the directly-follows graph induced by an event log, with an approach to identify combinations of split gateways that accurately capture the concurrency, conflict and causal relations between neighbors in the graph.
Journal ArticleDOI
Process compliance analysis based on behavioural profiles
TL;DR: It is argued that a behavioural abstraction may be leveraged to measure the compliance of a process log - a collection of cases to utilise causal behavioural profiles that capture the behavioural characteristics of process models and cases, and can be computed efficiently.
Journal Article
Process compliance analysis based on behavioural profiles
TL;DR: In this article, a behavioural abstraction is leveraged to measure the compliance of a process log, i.e., a collection of cases, and different compliance measures based on these profiles are proposed.
Journal Article
Semantic querying of business process models
TL;DR: This paper proposes an automated approach for querying a business process model repository for structurally and semantically relevant models and provides abusiness process model search engine implementation for evaluation of the proposed approach.