Efficient and Customisable Declarative Process Mining with SQL View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Stefan Schönig , Andreas Rogge-Solti , Cristina Cabanillas , Stefan Jablonski , Jan Mendling

ABSTRACT

Flexible business processes can often be modelled more easily using a declarative rather than a procedural modelling approach. Process mining aims at automating the discovery of business process models. Existing declarative process mining approaches either suffer from performance issues with real-life event logs or limit their expressiveness to a specific set of constaint types. Lately, RelationalXES, a relational database architecture for storing event log data, has been introduced. In this paper, we introduce a mining approach that directly works on relational event data by querying the log with conventional SQL. By leveraging database performance technology, the mining procedure is fast without limiting itself to detecting certain control-flow constraints. Queries can be customised and cover process perspectives beyond control flow, e.g., organisational aspects. We evaluated the performance and the capabilities of our approach with regard to several real-life event logs. More... »

PAGES

290-305

References to SciGraph publications

  • 2011. Process Mining, Discovery, Conformance and Enhancement of Business Processes in NONE
  • 2006. A Declarative Approach for Flexible Business Processes Management in BUSINESS PROCESS MANAGEMENT WORKSHOPS
  • 2013. Discovering Data-Aware Declarative Process Models from Event Logs in BUSINESS PROCESS MANAGEMENT
  • 2013. Enhancing Declare Maps Based on Event Correlations in BUSINESS PROCESS MANAGEMENT
  • 2009-05. Declarative workflows: Balancing between flexibility and support in COMPUTER SCIENCE - RESEARCH AND DEVELOPMENT
  • 2015. Ensuring Model Consistency in Declarative Process Discovery in BUSINESS PROCESS MANAGEMENT
  • 2012. Efficient Discovery of Understandable Declarative Process Models from Event Logs in ACTIVE FLOW AND COMBUSTION CONTROL 2018
  • 2011. XES, XESame, and ProM 6 in PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS
  • 2015. Mining the Organisational Perspective in Agile Business Processes in ENTERPRISE, BUSINESS-PROCESS AND INFORMATION SYSTEMS MODELING
  • 2013. A Knowledge-Based Integrated Approach for Discovering and Repairing Declare Maps in ADVANCED INFORMATION SYSTEMS ENGINEERING
  • 2005. Workflow Resource Patterns: Identification, Representation and Tool Support in ACTIVE FLOW AND COMBUSTION CONTROL 2018
  • 1998. Organisationsverwaltung in Workflow-Management-Systemen in NONE
  • 2012. Imperative versus Declarative Process Modeling Languages: An Empirical Investigation in BUSINESS PROCESS MANAGEMENT WORKSHOPS
  • Book

    TITLE

    Advanced Information Systems Engineering

    ISBN

    978-3-319-39695-8
    978-3-319-39696-5

    From Grant

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-39696-5_18

    DOI

    http://dx.doi.org/10.1007/978-3-319-39696-5_18

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1045579557


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