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dc.contributor.authorChatain, Thomas
dc.contributor.authorCarmona Vargas, Josep
dc.contributor.authorDongen, Boudewijn F. van
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2019-01-31T08:34:19Z
dc.date.available2019-01-31T08:34:19Z
dc.date.issued2017
dc.identifier.citationChatain, T.; Carmona, J.; Dongen, B. Alignment-based trace clustering. A: International Conference on Conceptual Modeling. "Conceptual Modeling, 36th International Conference, ER 2017: Valencia, Spain, November 6-9, 2017: proceedings". Berlín: Springer, 2017, p. 295-308.
dc.identifier.isbn978-3-319-69904-2
dc.identifier.urihttp://hdl.handle.net/2117/127952
dc.description.abstractA novel method to cluster event log traces is presented in this paper. In contrast to the approaches in the literature, the clustering approach of this paper assumes an additional input: a process model that describes the current process. The core idea of the algorithm is to use model traces as centroids of the clusters detected, computed from a generalization of the notion of alignment. This way, model explanations of observed behavior are the driving force to compute the clusters, instead of current model agnostic approaches, e.g., which group log traces merely on their vector-space similarity. We believe alignment-based trace clustering provides results more useful for stakeholders. Moreover, in case of log incompleteness, noisy logs or concept drift, they can be more robust for dealing with highly deviating traces. The technique of this paper can be combined with any clustering technique to provide model explanations to the clusters computed. The proposed technique relies on encoding the individual alignment problems into the (pseudo-)Boolean domain, and has been implemented in our tool DarkSider that uses an open-source solver.
dc.format.extent14 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Informàtica::Informàtica teòrica
dc.subject.lcshCluster analysis
dc.subject.otherModel explanations
dc.subject.otherGroup log
dc.subject.otherIndividual alignment problems
dc.subject.otherCluster event log
dc.subject.otherClustering approach
dc.titleAlignment-based trace clustering
dc.typeConference report
dc.subject.lemacAnàlisi de conglomerats
dc.contributor.groupUniversitat Politècnica de Catalunya. ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals
dc.identifier.doi10.1007/978-3-319-69904-2_24
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-319-69904-2_24
dc.rights.accessOpen Access
local.identifier.drac23568140
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TIN2013-46181-C2-1-R
local.citation.authorChatain, T.; Carmona, J.; Dongen, B.
local.citation.contributorInternational Conference on Conceptual Modeling
local.citation.pubplaceBerlín
local.citation.publicationNameConceptual Modeling, 36th International Conference, ER 2017: Valencia, Spain, November 6-9, 2017: proceedings
local.citation.startingPage295
local.citation.endingPage308


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