Share Your Research, Maximize Your Social Impacts
Churn Prediction using MAPREDUCE
Journal: International Journal of Scientific Engineering and Technology (IJSET) (Vol.3, No. 5)Publication Date: 2014-05-01
Authors : S. Ezhilmathi Sonia; S. Brintha Rajakumar; C. Nalini;
Page : 597-600
Keywords : Hadoop MapReduce; Telecommunication; Churn Analysis; Data mining;
Source : Download
Find it from : Google Scholar
Abstract
The data mining process to identify churners has concern with size of the dataset. This paper analyzes the telecom customer complaints and call quality datasets using Mapreduce to predict the customer churn. HDFS and Mapreduce make it possible to mine larger data sets without the constraints of the data size.
Other Latest Articles
- Effect of Fly Ash and PhosphoGypsum on Properties of Expansive Soils
- Accelerometer-based Wave Motion Compensation on Ship Mounted Weaponryrial
- Solar Distillation Using Nano-Material
- A synchronized Scheduler/Reminder Application for Philips 2KTV with Joint SPACE platform
- Six Sigma Methodology Utilization in Medical Transcription-A DMAIC Process to Identify Six Sigma Projects
Last modified: 2014-09-27 23:55:14