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Autor(en): 
  • Henrik Leopold
  • Natural Language in Business Process Models: Theoretical Foundations, Techniques, and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Dezember 2013  
    Genre:  Wirtschaft / Recht 
     
    ArtificialIntelligence / BPM / BusinessProcessManagement / businessprocessmodeling / Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften / Computerlinguistik und Korpuslinguistik / Linguistics / NaturalLanguageProcessing
    ISBN:  9783319041742 
    EAN-Code: 
    9783319041742 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #168 - Lecture Notes in Business Information Processing  
    Dimensionen:  H 235 mm / B 155 mm / D 12 mm 
    Gewicht:  318 gr 
    Seiten:  204 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Natural language is one of the most important means of human communication. It enables us to express our will, to exchange thoughts, and to document our knowledge in written sources. Owing to its substantial role in many facets of human life, technology for automatically analyzing and processing natural language has recently become increasingly important. In fact, natural language processing tools have paved the way for entirely new business opportunities.

    The goal of this book is to facilitate the automatic analysis of natural language in process models and to employ this analysis for assisting process model stakeholders. Therefore, a technique is defined that automatically recognizes and annotates process model element labels. In addition, this technique is leveraged to support organizations in effectively utilizing their process models in various ways.

    The book is organized into seven chapters. It starts with an overview of business process management and linguistics and continues with conceptual contributions on parsing and annotating process model elements, with the detection and correction of process model guideline violations, with the generation of natural language from process models, and finally ends with the derivation of service candidates from process models.

      



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