Comparative Analysis of Machine Learning Algorithms on IVR data

T.S, Aswin. and Batra, Himanshu and Ramachandran, Mathangi (2018) Comparative Analysis of Machine Learning Algorithms on IVR data. EAI Endorsed Transactions on Energy Web, 5 (18): e4. ISSN 2032-944X

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We aim to classify IVR data (Interactive Voice Response) and provide a detailed summary of the methods and techniques we employed to create a classifier model of reasonably high accuracy. This model is built to process large datasets of customer grievance lines (in IVR form converted to text), clustering and classifying these lines as accurately as possible. Here machine learning algorithms have been used to build text classifier models, in both supervised and unsupervised approaches on IVR datasets, and their labels have been checked for accuracy. Documentation of the methods applied gives insight into how best we can extract meaningful information and perform classification. By ensuring optimization in the classification of large datasets, resources like time, money and human effort are saved in the long run, and the data is more purposeful.

Item Type: Article
Uncontrolled Keywords: IVR data classification, machine learning on IVR data, text classification, analysis of machine learning methods
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 23 Sep 2020 13:29
Last Modified: 23 Sep 2020 13:29

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