TY  - BOOK
AU  - Leopold,Henrik
ED  - SpringerLink (Online service)
TI  - Natural Language in Business Process Models: Theoretical Foundations, Techniques, and Applications 
T2  - Lecture Notes in Business Information Processing,
SN  - 9783319041759
AV  - HF54.5-54.56 
U1  - 650 23
PY  - 2013///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Business
KW  - Information technology
KW  - Data processing
KW  - Computational linguistics
KW  - Application software
KW  - Business and Management
KW  - IT in Business
KW  - Language Translation and Linguistics
KW  - Information Systems Applications (incl. Internet)
KW  - Computational Linguistics
KW  - Computer Appl. in Administrative Data Processing
N1  - 1 Business Process Management -- 2 Linguistics -- 3 Parsing and Annotating Process Model Elements -- 4 Detecting and Correcting Linguistic Guideline Violations -- 5 Generation of Natural Language Texts from Process Models -- 6 Service Derivation from Process Models -- 7 Conclusion
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-319-04175-9
ER  -