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dc.contributor.authorMokhov, Andrey
dc.contributor.authorCarmona Vargas, Josep
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2016-03-09T08:21:30Z
dc.date.available2016-03-09T08:21:30Z
dc.date.issued2015
dc.identifier.citationMokhov, A., Carmona, J. Event log visualisation with conditional partial order graphs: from control flow to data. A: International Workshop on Algorithms & Theories for the Analysis of Event Data. "Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data: Brussels, Belgium, June 22-23, 2015". Bruselas: CEUR-WS.org, 2015, p. 16-30.
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/2117/84016
dc.description.abstractProcess mining techniques rely on event logs: the extraction of a process model (discovery) takes an event log as the input, the adequacy of a process model (conformance) is checked against an event log, and the enhancement of a process model is performed by using available data in the log. Several notations and formalisms for event log representation have been proposed in the recent years to enable efficient algorithms for the aforementioned process mining problems. In this paper we show how Conditional Partial Order Graphs (CPOGs), a recently introduced formalism for compact representation of families of partial orders, can be used in the process mining field, in particular for addressing the problem of compact and easy-to-comprehend visualisation of event logs with data. We present algorithms for extracting both the control flow as well as the relevant data parameters from a given event log and show how CPOGs can be used for efficient and effective visualisation of the obtained results. We demonstrate that the resulting representation can be used to reveal the hidden interplay between the control and data flows of a process, thereby opening way for new process mining techniques capable of exploiting this interplay.
dc.format.extent15 p.
dc.language.isoeng
dc.publisherCEUR-WS.org
dc.subjectÀrees temàtiques de la UPC::Informàtica::Informàtica teòrica
dc.subject.lcshInformation visualization
dc.subject.lcshData mining
dc.subject.lcshAlgorithms
dc.titleEvent log visualisation with conditional partial order graphs: from control flow to data
dc.typeConference report
dc.subject.lemacVisualització de la informació
dc.subject.lemacMineria de dades
dc.subject.lemacAlgorismes
dc.contributor.groupUniversitat Politècnica de Catalunya. ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ceur-ws.org/Vol-1371/paper02.pdf
dc.rights.accessOpen Access
local.identifier.drac17510126
dc.description.versionPostprint (author's final draft)
local.citation.authorMokhov, A.; Carmona, J.
local.citation.contributorInternational Workshop on Algorithms & Theories for the Analysis of Event Data
local.citation.pubplaceBruselas
local.citation.publicationNameProceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data: Brussels, Belgium, June 22-23, 2015
local.citation.startingPage16
local.citation.endingPage30


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