Text Mining for Effective Classification of Car Problem Severity Levels

Authors

Rajesh Timmisetty, Webster UniversityFollow
Prudhvi Aluri, Webster UniversityFollow
Dimple Chintala, Webster UniversityFollow
Hema Sanaka, Webster UniversityFollow

Abstract

This research proposes a machine-learning approach to enhance customer satisfaction in the automotive service industry by classifying the severity of car problems based on customer descriptions using the text-mining concept. Using a dataset of labeled car service problem statements, the study employs supervised classification models using text mining, emphasizing the decision tree model for its superior performance. The aim is to empower service centers to offer pre-diagnoses, fostering loyalty even for non-severe issues. The study contributes to the intersection of machine learning and automotive services, providing a more effective and customer-centric diagnostic approach.

Recommended Citation

Timmisetty, Rajesh; Aluri, Prudhvi; Chintala, Dimple; and Sanaka, Hema, "Text Mining for Effective Classification of Car Problem Severity Levels" (2024). MWAIS 2024 Proceedings. 34.
https://aisel.aisnet.org/mwais2024/34