Topic Detection for Customer Support Queries
Huyberechts, Liam (2023)
2023
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2023060621907
https://urn.fi/URN:NBN:fi:amk-2023060621907
Tiivistelmä
This study investigates the efficacy and utilization of artificial intelligence in the customer service sector by implementing topic detection for customer support queries to identify underlying topics within past questions.
Most importantly, findings of the efficacy of such a system and the prerequisite work needed to implement it are reflected in the thesis. As well as the potential improvements and issues which could arise from its implementation, namely, the need to collect large amounts of quality data.
With reference to books, scientific papers, and documentation – the findings and implementation of a topic detection system are presented, along with the technical understanding and potential influence topic detection can have with regards to customer support.
Finally, the development results display the testing methodology and metrics used when assessing the use of an implementation of topic detection for customer support queries.
Most importantly, findings of the efficacy of such a system and the prerequisite work needed to implement it are reflected in the thesis. As well as the potential improvements and issues which could arise from its implementation, namely, the need to collect large amounts of quality data.
With reference to books, scientific papers, and documentation – the findings and implementation of a topic detection system are presented, along with the technical understanding and potential influence topic detection can have with regards to customer support.
Finally, the development results display the testing methodology and metrics used when assessing the use of an implementation of topic detection for customer support queries.