A
Adriano Augusto
Researcher at University of Melbourne
Publications - 36
Citations - 893
Adriano Augusto is an academic researcher from University of Melbourne. The author has contributed to research in topics: Process mining & Business process discovery. The author has an hindex of 11, co-authored 30 publications receiving 632 citations. Previous affiliations of Adriano Augusto include Polytechnic University of Turin & Queensland University of Technology.
Papers
More filters
Journal ArticleDOI
Automated Discovery of Process Models from Event Logs: Review and Benchmark
Adriano Augusto,Raffaele Conforti,Marlon Dumas,Marcello La Rosa,Fabrizio Maria Maggi,Andrea Marrella,Massimo Mecella,Allar Soo +7 more
TL;DR: The results highlight gaps and unexplored tradeoffs in the field, including the lack of scalability of some methods and a strong divergence in their performance with respect to the different quality metrics used.
Posted Content
Automated Discovery of Process Models from Event Logs: Review and Benchmark
Adriano Augusto,Raffaele Conforti,Marlon Dumas,Marcello La Rosa,Fabrizio Maria Maggi,Andrea Marrella,Massimo Mecella,Allar Soo +7 more
TL;DR: In this paper, a systematic review and comparative evaluation of automated process discovery methods, using an open-source benchmark and covering twelve publicly-available real-life event logs, twelve proprietary real life event logs and nine quality metrics, is presented.
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.
Proceedings ArticleDOI
Split Miner: Discovering Accurate and Simple Business Process Models from Event Logs
TL;DR: In this paper, an automated process discovery method that produces simple process models with low branching complexity and consistently high and balanced fitness, precision and generalization, while achieving execution times 2-6 times faster than state-of-the-art methods on a set of 12 real-life logs is presented.
Proceedings Article
Split Miner: Automated Discovery of Accurate and Simple Business Process Models from Event Logs
TL;DR: Split Miner is the first automated process discovery method that is guaranteed to produce deadlock-free process models with concurrency, while not being restricted to producing block-structured process models.