Abstract: Churn prediction is considered a big issue in the Telecom market because customer acquisition costs five to eight times than retaining an existing one. Customer retention is the action that a service provider undertakes in order to reduce customer dissatisfaction and decrease the probability of leaving a service provider. This paper proposes a churn prediction retention framework based on data mining techniques. Deploying the proposed framework into a business intelligence system can help in enhancing the efficiency of customer relationship management. Moreover it can help customer churn management department to easily predict and retain the expected future churners in many business areas. The proposed framework mainly composed of seven phases and sub-phases. A case study is demonstrated to evaluate the framework throughout 5000 customers’ records in an anonymous telecom company.

• Publication Date: 29-Dec-2015
• DOI: 10.15224/978-1-63248-082-8-06
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Abstract: The simultaneous transmissions of multiple users on a channel interfere with each other and it becomes pivotal to devise a mechanism to obtain some form of separation. In a cognitive radio ad hoc network (CRAHN), the users compete to acquire best suitable bandwidth from already scarce spectrum, resulting in a fierce competition. The nodes may not observe desirable etiquettes in selecting channels and waveforms that result in chaos, which degrades the Quality of Service for the entire network. In order to inhibit the nodes while maintaining their autonomous behavior, there is a need of intelligent mechanism to inculcate the nodes in the network. A game theoretic framework is proposed to achieve convergence in selecting sub-channels and waveforms for transmissions. The proposed model is an eigen-iterative framework, in which signature sequences and sub-channels keep on updating after every cycle. Eigenvectors corresponding to the minimum eigenvalue of correlation matrix is used to maximi

• Publication Date: 29-Dec-2015
• DOI: 10.15224/978-1-63248-082-8-07
• Views: 0
• Downloads: 0