Leveraging Unstructured Data to Analyze Implicit Process Context View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-08-12

AUTHORS

Renuka Sindhgatta , Aditya Ghose , Hoa Khanh Dam

ABSTRACT

Adapting a business process to different context requires identifying various situations and evolving the process to support such situations. Previous work focused on modeling, observing and collecting contextual information. Furthermore, impact of context on process or resource performance has been studied. However, much of the work considers explicit contextual information that is defined by domain experts. There are several implicit contextual dimensions, that are difficult to model as all situations cannot be anticipated a priori. Context mining involves analysis of process logs to identify context and correlate with process performance indicators or outcomes. In this work, we leverage unstructured data available in user comments or mails to discover implicit context of the process. We automatically analyze textual data and group process instances by applying information extraction and text clustering techniques. Groups of process instances are correlated to their process outcomes to filter irrelevant information. We apply the approach on real-world process logs to identify contextual information. More... »

PAGES

143-158

References to SciGraph publications

  • 2004. Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition in INTELLIGENT INFORMATION PROCESSING AND WEB MINING
  • 2004-02. What we talk about when we talk about context in PERSONAL AND UBIQUITOUS COMPUTING
  • 2016. Predictive Business Process Monitoring with Structured and Unstructured Data in BUSINESS PROCESS MANAGEMENT
  • 2010. Learning the Context of a Clinical Process in BUSINESS PROCESS MANAGEMENT WORKSHOPS
  • 2012. Defining Process Performance Indicators by Using Templates and Patterns in BUSINESS PROCESS MANAGEMENT
  • 2016. Context-Aware Analysis of Past Process Executions to Aid Resource Allocation Decisions in ADVANCED INFORMATION SYSTEMS ENGINEERING
  • 2016. Context-Aware Recommendation of Task Allocations in Service Systems in SERVICE-ORIENTED COMPUTING
  • 2010. A Formal Model for Process Context Learning in BUSINESS PROCESS MANAGEMENT WORKSHOPS
  • 2011. Process Model Generation from Natural Language Text in ACTIVE FLOW AND COMBUSTION CONTROL 2018
  • Book

    TITLE

    Business Process Management Forum

    ISBN

    978-3-319-98650-0
    978-3-319-98651-7

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-98651-7_9

    DOI

    http://dx.doi.org/10.1007/978-3-319-98651-7_9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1106120934


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