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Free Download A Big Data Clustering Algorithm For Mitigating The Risk Of Customer Churn Project in Java Spring Framework with source code

Java Spring Framework project   Publish on -  2018-07-11
kalai selvi
php, java, big data, Html,Css,Javascript, Jquery 
1 Reviews 5
2695 View
115 Downloads

A Big Data Clustering Algorithm For Mitigating The Risk Of Customer Churn project is a desktop application which is developed in Java Spring Framework platform. This Java Spring Framework project with tutorial and guide for developing a code. A Big Data Clustering Algorithm For Mitigating The Risk Of Customer Churn is a open source you can Download zip and edit as per you need. If you want more latest Java Spring Framework projects here. This is simple and basic level small project for learning purpose. Also you can modified this system as per your requriments and develop a perfect advance level project. Zip file containing the source code that can be extracted and then imported into Eclipse. This Source code for BE, BTech, MCA, BCA, Engineering, Bs.CS, IT, Software Engineering final year students can submit in college. This script developed by kalai selvi. This desktop application 100% working smooth without any bug. It is developed using java,hadoop and Database hdfs. This software code helpful in academic projects for final year students. We have a great collection of Java Spring Framework projects.

Document and Reports information

This doucment file contains project Synopsis, Reports, and various diagrams. Also abstract pdf file inside zip so that document link below the page. Class Diagrams, Use Case Diagrams, Entity–relationship(ER) Diagrams, Data flow diagram(DFD), Sequence diagram and software requirements specification (SRS) in report file. Complete ready made open source code free of cost download. You can find Top Downloaded Java Spring Framework projects here.

About Project

project Name A Big Data Clustering Algorithm For Mitigating The Risk Of Customer Churn
project ID 2436
Developer Name kalai selvi
Publish Date 2018-07-11
project Platform Java Spring Framework
Programming Language java,hadoop
Front End 
Back End 
IDE Tool Eclipse
project Earning kalai selvi Earn Rs.0 from this project.
Database hdfs
project Type desktop Application
No of project Download 115
project Total View 2695
Today Trends 40
Current Month Trends 59
Last Month Trends 51

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Features of the Project

As market competition intensifies, customer churn management is increasingly becoming an important means of competitive advantage for companies. However, when dealing with big data in the industry, existing churn prediction models cannot work very well. In addition, decision makers are always faced with imprecise operations management. In response to these difficulties, a new clustering algorithm called Semantic Driven Subtractive Clustering Method (SDSCM) is proposed. Experimental results indicate that SDSCM has stronger clustering semantic strength than Subtractive Clustering Method (SCM) and fuzzy c-means (FCM). Then a parallel SDSCM algorithm is implemented through a Hadoop MapReduce framework. In the case study, the proposed parallel SDSCM algorithm enjoys a fast running speed when compared with the other methods. Furthermore, We provide some marketing strategies in accordance with the clustering results, and a simplified marketing activity is simulated to ensure profit maximization.

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