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dc.contributor.authorAugusto, A
dc.contributor.authorConforti, R
dc.contributor.authorArmas-Cervantes, A
dc.contributor.authorDumas, M
dc.contributor.authorLa Rosa, M
dc.date.available2019-01-03T02:22:54Z
dc.date.issued2020
dc.identifier.citationAugusto, A., Conforti, R., Armas-Cervantes, A., Dumas, M. & La Rosa, M. (2020). Measuring Fitness and Precision of Automatically Discovered Process Models: A Principled and Scalable Approach. IEEE Transactions on Knowledge and Data Engineering, PP (99), pp.1-1. https://doi.org/10.1109/tkde.2020.3003258.
dc.identifier.issn1041-4347
dc.identifier.urihttp://hdl.handle.net/11343/219723
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.titleMeasuring Fitness and Precision of Automatically Discovered Process Models: A Principled and Scalable Approach
dc.typeJournal Article
dc.identifier.doi10.1109/tkde.2020.3003258
melbourne.affiliation.departmentComputing and Information Systems
melbourne.source.titleIEEE Transactions on Knowledge and Data Engineering
melbourne.source.volumePP
melbourne.source.issue99
melbourne.source.pages1-1
melbourne.elementsid1363933
melbourne.contributor.authorAugusto, Adriano
melbourne.contributor.authorArmas Cervantes, Abel
melbourne.contributor.authorReissner, Daniel
dc.identifier.eissn1558-2191
melbourne.accessrightsOpen Access


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