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  4. Cooperation of Human and Active Learning based AI for Fast and Precise Complaint Management
 
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2022
Conference Paper
Title

Cooperation of Human and Active Learning based AI for Fast and Precise Complaint Management

Abstract
In highly competitive markets, customer loyalty plays an increasingly important role for companies. An important aspect is the recording and processing of customer complaints, on the one hand for problem-solving and on the other hand for internal process optimization. The complaint handling process extends over several phases, in which different people with varying expertise and experience may be involved, which poses a major challenge in order to achieve Consistent quality in the recording process of complaints. To address this issue, this work presents a robust active learning based AI system that allows using existing expert knowledge to create more reliable classifications in a shorter amount of time. The implemented prototype shows a decrease of up to 86% in the average processing time of complaints, with an average increase of up to 37% in the classification accuracy.
Author(s)
Hennebold, Christoph  
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA  
Mei, Xiaodong
Mailahn, Ortwin
Huber, Marco  
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA  
Mannuß, Oliver  
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA  
Mainwork
IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022. Proceedings  
Conference
International Conference on Systems, Man, and Cybernetics 2022  
DOI
10.1109/SMC53654.2022.9945445
Language
English
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA  
Keyword(s)
  • active learning

  • artificial intelligence

  • classification

  • complaint management

  • machine learning

  • quality management

  • uncertainty distribution

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