Journal ArticleDOI
Data-driven and automated prediction of service level agreement violations in service compositions
TLDR
This paper discusses data-driven, statistical approaches for both, instance-level prediction (SLA compliance prediction for an ongoing business process instance) and forecasting (compliance prediction for future instances) and presents an integrated framework and numerically evaluates the approach based on a case study from the manufacturing domain.Abstract:
Service Level Agreements (SLAs), i.e., contractually binding agreements between service providers and clients, are gaining momentum as the main discriminating factor between service implementations. For providers, SLA compliance is of utmost importance, as violations typically lead to penalty payments or reduced customer satisfaction. In this paper, we discuss approaches to predict violations a priori. This allows operators to take timely remedial actions, and prevent SLA violations before they have occurred. We discuss data-driven, statistical approaches for both, instance-level prediction (SLA compliance prediction for an ongoing business process instance) and forecasting (compliance prediction for future instances). We present an integrated framework, and numerically evaluate our approach based on a case study from the manufacturing domain.read more
Citations
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Journal ArticleDOI
Predictive Monitoring of Business Processes: A Survey
TL;DR: The different types of computational predictive methods, such as statistical techniques or machine learning approaches, and certain aspects as the type of predicted values and quality evaluation metrics, have been considered for the categorization of these methods.
Journal ArticleDOI
Comparing and Combining Predictive Business Process Monitoring Techniques
Andreas Metzger,Philipp Leitner,Dragan Ivanovic,Eric Schmieders,Rod Franklin,Manuel Carro,Schahram Dustdar,Klaus Pohl +7 more
TL;DR: This work empirically analyzes and compares three main classes of predictive monitoring techniques, which are based on machine learning, constraint satisfaction, and Quality-of-Service (QoS) aggregation, and indicates that certain combinations of techniques may outperform individual techniques with respect to specific accuracy indicators.
Journal Article
Business Process Management: A Survey
TL;DR: In this paper, the authors demystify the acronyms in this domain, describe the state-of-theart technology, and argue that BPM could benefit from formal methods/languages (cf. Petri nets, process algebras, etc.).
References
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Journal Article
R: A language and environment for statistical computing.
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Book
C4.5: Programs for Machine Learning
TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
Book
Time series analysis, forecasting and control
TL;DR: In this article, a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970 is presented, focusing on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.
Journal ArticleDOI
The WEKA data mining software: an update
TL;DR: This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
Journal ArticleDOI
Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.