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dc.contributor.authorCarmona Vargas, Josep
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2020-02-28T11:16:44Z
dc.date.available2020-03-07T01:26:19Z
dc.date.issued2018
dc.identifier.citationCarmona, J. Decomposed process discovery and conformance checking. A: "Encyclopedia of big data technologies 2019". Berlín: Springer, 2018, p. 1-7.
dc.identifier.isbn978-3-319-63962-8
dc.identifier.urihttp://hdl.handle.net/2117/178875
dc.description.abstractDecomposed process discovery and decomposed conformance checking are the corresponding variants of the two monolithic fundamental problems in process mining (van der Aalst 2011): automated process discovery, which considers the problem of discovering a process model from an event log (Leemans 2009), and conformance checking, which addresses the problem of analyzing the adequacy of a process model with respect to observed behavior (Munoz-Gama 2009), respectively. The term decomposed in the two definitions is mainly describing the way the two problems are tackled operationally, to face their computational complexity by splitting the initial problem into smaller problems, that can be solved individually and often more efficiently.
dc.format.extent7 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
dc.subject.lcshData mining
dc.subject.lcshComputational complexity
dc.subject.otherProcess mining
dc.subject.otherAutomated process discovery
dc.subject.otherConformance checking
dc.titleDecomposed process discovery and conformance checking
dc.typePart of book or chapter of book
dc.subject.lemacMineria de dades
dc.subject.lemacComplexitat computacional
dc.contributor.groupUniversitat Politècnica de Catalunya. ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals
dc.identifier.doi10.1007/978-3-319-63962-8_95-1
dc.relation.publisherversionhttps://link.springer.com/referencework/10.1007/978-3-319-63962-8
dc.rights.accessOpen Access
local.identifier.drac27008994
dc.description.versionPostprint (author's final draft)
local.citation.authorCarmona, J.
local.citation.pubplaceBerlín
local.citation.publicationNameEncyclopedia of big data technologies 2019
local.citation.startingPage1
local.citation.endingPage7


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