Natural Language in Business Process Models : Theoretical Foundations, Techniques, and Applications
Book Details
Format
Paperback / Softback
Book Series
Lecture Notes in Business Information Processing
ISBN-10
3319041746
ISBN-13
9783319041742
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Dec 16th, 2013
Print length
181 Pages
Product Classification:
Computational and corpus linguisticsComputational linguisticsSocial research & statisticsSocial research and statisticsBusiness mathematics & systemsBusiness mathematics and systemsDigital and Information technology: general topicsInformation technology: general issuesBusiness applicationsNatural language & machine translationNatural language and machine translation
Ksh 8,100.00
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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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