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000825963 24500 $$aData-Driven Process Discovery and Analysis :$$b6th IFIP WG 2.6 International Symposium, SIMPDA 2016, Graz, Austria, December 15-16, 2016, Revised Selected Papers /$$cedited by Paolo Ceravolo, Christian Guetl, Stefanie Rinderle-Ma.
000825963 264_1 $$aCham :$$bSpringer International Publishing :$$bImprint: Springer,$$c2018.
000825963 300__ $$a1 online resource (ix, 97 pages) :$$billustrations.
000825963 336__ $$atext$$btxt$$2rdacontent
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000825963 4901_ $$aLecture Notes in Business Information Processing,$$x1865-1348 ;$$v307
000825963 5050_ $$aModel and Event Log Reductions to Boost the Computation of Alignments -- Translating BPMN to Business Rules -- Execution-based Model Profiling -- DB-XES: Enabling Process Discovery in the Large -- Extracting Service Process Models from Location Data.#xE000;
000825963 506__ $$aAccess limited to authorized users.
000825963 520__ $$aThis book constitutes the revised selected papers from the 6th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2016, held in Graz, Austria in December 2016. The 5 papers presented in this volume were carefully reviewed and selected from 18 submissions. In this edition, the presentations focused on the adoption of process mining algorithms for continuous monitoring of business process. They underline the most relevant challenges identified and propose novel solutions for their resolution.
000825963 650_0 $$aComputer science.
000825963 650_0 $$aManagement information systems.
000825963 650_0 $$aIndustrial management.
000825963 650_0 $$aData mining.
000825963 650_0 $$aApplication software.
000825963 7001_ $$aCeravolo, Paolo.$$eeditor.
000825963 7001_ $$aGuetl, Christian.$$eeditor.
000825963 7001_ $$aRinderle-Ma, Stefanie.$$eeditor.
000825963 77608 $$iPrint version: $$z9783319741604
000825963 830_0 $$aLecture notes in business information processing ;$$v307.
000825963 852__ $$bebk
000825963 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-74161-1$$zOnline Access$$91397441.1
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