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2013 | Book

Business Process Management Read chapter Read first chapter

Natural Language in Business Process Models

Theoretical Foundations, Techniques, and Applications

Editor: Henrik Leopold

Publisher: Springer International Publishing

Book Series : Lecture Notes in Business Information Processing

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

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.

Table of Contents

Frontmatter
Business Process Management
Abstract
Business process management (BPM) represents one of the core concepts enabling companies to flexibly react to the constantly changing business environment. The actual relevance of business process management is, for instance, illustrated by the size of the BPM software market. A recent study of Global Industry Analysts forecasts that the global market for BPM software will reach a volume of over 5 billion US dollars by the year 2017 [18]. The importance of BPM in academia is demonstrated by its constant presence among top-ranked information system conferences [32, 2, 1, 271]. In fact, this also highlights that BPM has become one of the core areas of information systems research. The range of addressed topics goes from general organizational aspects of BPM to specific technical issues concerning business process models. Due to the importance of business process models for documenting and redesigning the operations of companies, many researchers have focused on aspects of process model design and process model quality. Nevertheless, there are still many significant aspects that have not been addressed by prior research.
Henrik Leopold
Linguistics
Abstract
This chapter provides an introduction into the field of linguistics. In order to lay the groundwork for the subsequent chapters of this book, we focus on three main aspects. First, Section 2.1 explains the basic concepts of linguistics and introduces the different schools of thought. Then, Section 2.2 gives an overview of theoretical linguistics. In particular, it discusses the different branches of theoretical linguistics such as morphology, syntax, and semantics. Using the insights from this section, we can adequately describe and analyze the natural language phenomena in business process models. Subsequently, Section 2.3 introduces the field of natural language processing. Specifically, it presents theoretical foundations for analyzing natural language in an automated fashion. Finally, Section 2.5 concludes the chapter with a summary.
Henrik Leopold
Parsing and Annotating Process Model Elements
Abstract
The aim of this book is to provide the means for exploiting and analyzing the linguistic information that is captured by process models. This chapter represents the first step in this direction by introducing a technique for automatically parsing and annotating process models. The technique can deal with the specific challenges of process model element labels and uses insights about grammatical structures and a tailored disambiguation algorithm to yield accurate results.
Henrik Leopold
Detecting and Correcting Linguistic Guideline Violations
Abstract
Due to the huge size of modeling initiatives in practice, many companies struggle with assuring the quality of their process model collections. While many model properties can already be checked automatically, there is a notable gap concerning techniques for checking linguistic aspects such as naming conventions for process model elements. In this chapter, we aim at closing this gap by introducing techniques for automatically detecting and correcting linguistic guideline violations. The presented approaches build on the parsing techniques defined in the last chapter and facilitate a reliable and flexible detection and correction of guideline violations.
Henrik Leopold
Generation of Natural Language Texts from Process Models
Abstract
Process models are widely used for documenting and redesigning the operations of companies. The audience of these models ranges from well-trained system analysts and developers to casual staff members who are unexperienced in terms of modeling. Hence, most of the latter lack the ability to understand process model in detail. This is a particular problem as this impedes the usage of process models to the desired extent. In this chapter, we investigate in how far the concept of natural language generation can be adapted to process models in order to provide all staff members with a understandable process description. To this end, we define an approach which automatically transforms BPMN process models into understandable natural language texts.
Henrik Leopold
Service Derivation from Process Models
Abstract
Service-oriented Architecture has been discussed for roughly a decade as a concept to increase the agility of a company in providing goods and services to external partners and organizing internal operations. Consequently, a plethora of approaches to service derivation have been defined in the past. A core problem is that many of these approaches lack methodological detail, and that none of them considers the consequent support using automatic analysis techniques. Hence, they do not scale up to the size of a whole company.
Henrik Leopold
Conclusion
Abstract
In this chapter, we summarize and discuss the results of this book. First, Section 7.1 summarizes the main findings. Afterwards, Section 7.2 discusses the implications of these findings before Section 7.1 gives an outlook on future research.
Henrik Leopold
Backmatter
Metadata
Title
Natural Language in Business Process Models
Editor
Henrik Leopold
Copyright Year
2013
Publisher
Springer International Publishing
Electronic ISBN
978-3-319-04175-9
Print ISBN
978-3-319-04174-2
DOI
https://doi.org/10.1007/978-3-319-04175-9

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