rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Data-Driven Process Discovery and Analysis
    sub title: 6th IFIP WG 2.6 International Symposium, SIMPDA 2016, Graz, Austria, December 15-16, 2016, Revised Selected Papers
  name:
    name part: Ceravolo, Paolo.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Guetl, Christian.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Rinderle-Ma, Stefanie.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: IX, 97 p. 46 illus. online resource.
  abstract: This 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.
  table of contents: Model 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. .
  note: edited by Paolo Ceravolo, Christian Guetl, Stefanie Rinderle-Ma.
  subject:
    topic: Data mining
  subject:
    topic: Management information systems
  subject:
    topic: Industrial management
  subject:
    topic: Application software
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Business Process Management
  subject:
    topic: Information Systems Applications (incl. Internet)
  subject:
    topic: Computer Appl. in Administrative Data Processing
  classification: QA76.9.D343
  classification: 006.312
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Business Information Processing, 307
  identifier: 9783319741611
  identifier: https://doi.org/10.1007/978-3-319-74161-1
  record info:
    record creation date: 180125
    record change date: 20191027151758.0
    record identifier: 978-3-319-74161-1