%0 Journal Article %1 D_2015 %A Limaye, Gauri D %A Chaudhary, Jyoti P %A Punjabi, Prof. Sunil K %D 2015 %I Auricle Technologies, Pvt., Ltd. %J International Journal on Recent and Innovation Trends in Computing and Communication %K C4.5 Churn HBase Hadoop MapReduce Prediction %N 3 %P 1699--1703 %R 10.17762/ijritcc2321-8169.1503175 %T Churn Prediction using MapReduce and HBase %U http://dx.doi.org/10.17762/ijritcc2321-8169.1503175 %V 3 %X The mobile telecommunication market is rapidly increasing with numerous service providers stepping in the market. This makes the customer think to leave the service provided by one service provider and move to another service provider for some better offers. This project is an attempt to design and implement an application that can take Customer Records as input and give Customer churn prediction details as output. It will enable service provider to know in advance about the valuable customer who are about to churn. By merely giving customer data records as input, user can get the desired customer behaviour pattern, which is the churn output. The output obtained will basically distinguish the churners and the non-churners. The system is built using Apache Hadoop, Apache HBase and a Data Mining Algorithm under MapReduce code. The use of Hadoop framework makes it easy to process the large datasets containing the information of customers.

@article{D_2015, abstract = {The mobile telecommunication market is rapidly increasing with numerous service providers stepping in the market. This makes the customer think to leave the service provided by one service provider and move to another service provider for some better offers. This project is an attempt to design and implement an application that can take Customer Records as input and give Customer churn prediction details as output. It will enable service provider to know in advance about the valuable customer who are about to churn. By merely giving customer data records as input, user can get the desired customer behaviour pattern, which is the churn output. The output obtained will basically distinguish the churners and the non-churners. The system is built using Apache Hadoop, Apache HBase and a Data Mining Algorithm under MapReduce code. The use of Hadoop framework makes it easy to process the large datasets containing the information of customers.}, added-at = {2015-08-13T08:44:13.000+0200}, author = {Limaye, Gauri D and Chaudhary, Jyoti P and Punjabi, Prof. Sunil K}, biburl = {https://www.bibsonomy.org/bibtex/2034fa702d8bc724ae29f635dc533f036/ijritcc}, doi = {10.17762/ijritcc2321-8169.1503175}, interhash = {95fd5b1d9bd14e2d256d0e68121707b3}, intrahash = {034fa702d8bc724ae29f635dc533f036}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {C4.5 Churn HBase Hadoop MapReduce Prediction}, month = {march}, number = 3, pages = {1699--1703}, publisher = {Auricle Technologies, Pvt., Ltd.}, timestamp = {2015-08-13T08:44:13.000+0200}, title = {Churn Prediction using {MapReduce} and {HBase}}, url = {http://dx.doi.org/10.17762/ijritcc2321-8169.1503175}, volume = 3, year = 2015 }