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Association Rules for Anomaly Detection and Root Cause Analysis in Process Executions Read chapter Read first chapter

2018 | OriginalPaper | Chapter

AB Testing for Process Versions with Contextual Multi-armed Bandit Algorithms

Authors : Suhrid Satyal, Ingo Weber, Hye-young Paik, Claudio Di Ciccio, Jan Mendling

Published in: Advanced Information Systems Engineering

Publisher: Springer International Publishing

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Abstract

Business process improvement ideas can be validated through sequential experiment techniques like AB Testing. Such approaches have the inherent risk of exposing customers to an inferior process version, which is why the inferior version should be discarded as quickly as possible. In this paper, we propose a contextual multi-armed bandit algorithm that can observe the performance of process versions and dynamically adjust the routing policy so that the customers are directed to the version that can best serve them. Our algorithm learns the best routing policy in the presence of complications such as multiple process performance indicators, delays in indicator observation, incomplete or partial observations, and contextual factors. We also propose a pluggable architecture that supports such routing algorithms. We evaluate our approach with a case study. Furthermore, we demonstrate that our approach identifies the best routing policy given the process performance and that it scales horizontally.

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previous chapter Association Rules for Anomaly Detection and Root Cause Analysis in Process Executions
next chapter Filtering Spurious Events from Event Streams of Business Processes
Footnotes
1
https://​nginx.​org/​ Accessed 15-06-2017.
 
3
https://​redis.​io/​ Accessed 15-06-2017.
 
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Metadata
Title
AB Testing for Process Versions with Contextual Multi-armed Bandit Algorithms
Authors
Suhrid Satyal
Ingo Weber
Hye-young Paik
Claudio Di Ciccio
Jan Mendling
Copyright Year
2018
Book
Advanced Information Systems Engineering

Print ISBN: 978-3-319-91562-3

Electronic ISBN: 978-3-319-91563-0

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-91563-0_2

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