Classification of broadband network devices using text mining technique.

ABSTRACT: The Broadband Internet industry is highly competitive, with service providers investing heavily in network development to meet customer demands and competing on pricing. Effective cost management is crucial for profitability in this market. This work proposes a model for classifying broadband network devices based on text mining techniques applied to a device list from a leading broadband network company in Thailand. The device descriptions are used to generate a feature vector, which is then employed by a classification algorithm to categorize devices into core, access, and last mile hierarchies. Various algorithms including decision tree, naïve Bayes, Bayesian network, k-nearest neighbor, support vector machine, and deep neural network are compared, with support vector machine achieving

SUBMITTER: Ketcham M 

PROVIDER: S-EPMC10477059 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature