Natural Language In Business Process Models
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Natural Language in Business Process Models
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.
Linguistic Refactoring of Business Process Models
Author: Fabian Pittke
language: en
Publisher: Logos Verlag Berlin GmbH
Release Date: 2016-03-02
In the past decades, organizations had to face numerous challenges due to intensifying globalization, shorter innovation cycles and growing IT support. Business process management is seen as a comprehensive approach to address these challenges. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since organizations tend to have a huge number of such models, analysis techniques are required that ensure the quality of these process models in an automatic fashion. The goal of this doctoral thesis is the development of model refactoring techniques by integrating and applying concepts from the three main branches of theoretical linguistics: syntax, semantics, and pragmatics. The syntactical refactoring technique addresses linguistic issues that arise by expressing process behavior with natural language. The semantic refactoring technique reworks terminology with overlapping and synonymous meaning. The pragmatic refactoring technique provides recommendations for incompletely specified process models. All of the presented techniques have been evaluated with real-world process model repositories from various industries to demonstrate their applicability and efficiency.
Business Process Models
Driven by the need for a closer alignment of business and IT requirements, the role of business process models in the development of enterprise software systems has increased continuously. Similar to other software artifacts, process models are developed and refined in team environments by several stakeholders, resulting in different versions. These versions need to be merged in order to obtain an integrated process model. Existing solutions to this basic problem in the field of software configuration management are mainly limited to textual documents, e.g., source code. This monograph presents a generally applicable framework for process model change management, which provides easy-to-use comparison and merging capabilities for the integration of different process model versions. The framework supports popular modeling languages such as BPMN, BPEL, or UML Activity Diagrams. Differences between process models are represented in terms of intuitive, high-level change operations. Equipped with a sophisticated analysis of dependencies and a semantic-aware computation of conflicts between differences, the framework constitutes a comprehensive and practically usable solution for process model change management in the model-driven development of enterprise software systems.