Practical Implementation of Machine Learning and Predictive Analytics in Cellular Network Transactions in Real Time

Dahj Muwawa Jean Nestor, Kingsley A. Ogudo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

In order to keep a high revenue stream, Communication Service Providers in general, Network Mobile Operators specifically need to ensure a good level of customer satisfaction by assigning a big weight on the user's Quality of Experience (QoE). With billions of transactions done by customers on both voice and data daily, Communication Service Providers (CSPs) shift the focus in studying customer behavior and data patterns to pinpoint opportunities to improve customer services, service quality and predict when customers are likely to terminate contracts, to perhaps move to another CSP. CSPs have managed to build efficient IT infrastructures to store customer transactions. These exist in many forms such as file systems, databases, etc. In this paper, a simplified predictive analytics is done using the (Customer Relationship Management) CRM information records to classify potential customers likely to terminate their contracts, using logistic regression and random forest models. The paper describes the process to build a simple predictive models to apply on a telecoms dataset.

Original languageEnglish
Title of host publication2018 International Conference on Advances in Big Data, Computing and Data Communication Systems, icABCD 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538630600
DOIs
Publication statusPublished - 13 Sept 2018
Externally publishedYes
Event2018 International Conference on Advances in Big Data, Computing and Data Communication Systems, icABCD 2018 - Durban, South Africa
Duration: 6 Aug 20187 Aug 2018

Publication series

Name2018 International Conference on Advances in Big Data, Computing and Data Communication Systems, icABCD 2018

Conference

Conference2018 International Conference on Advances in Big Data, Computing and Data Communication Systems, icABCD 2018
Country/TerritorySouth Africa
CityDurban
Period6/08/187/08/18

Keywords

  • Artificial Intelligence (AI)
  • CRM
  • CSP
  • Logistic Regression
  • Machine Learning
  • Predictive Analytics
  • Random Forest
  • Telecommunications

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management
  • Computer Networks and Communications
  • Artificial Intelligence

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