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

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...

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Bibliographic Details
Published in:	2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) pp. 282 - 287
Main Authors:	Hennebold, Christoph, Mei, Xiaodong, Mailahn, Ortwin, Huber, Marco F., Mannus, Oliver
Format:	Conference Proceeding
Language:	English
Published:	IEEE 09-10-2022
Subjects:	active learning Artificial intelligence classification Companies complaint management machine learning Optimization Problem-solving Prototypes quality management Recording Reliability uncertainty distribution
Online Access:	Get full text
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Summary:	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.
ISSN:	2577-1655
DOI:	10.1109/SMC53654.2022.9945445