Abstract
In order to mine specified telecom customers with special behaviours from vast voice communication records of Telecom company, a novel Hybrid Data Mining method of Telecom Customers (HDMTC) with special behaviours is proposed in this paper, which integrates Kmeans and XGBoost into one framework. First, AHP model helped to model the features of customers with special behaviours. Then, Due to semi-supervised methodology, Kmeans approach was improved by small amounts of tagged initial cluster centroids and weighted Euclidean distance. Improved Kmeans was utilized to tag the decision attribute of data to construct training dataset. After that, XGBoost model was trained via the training dataset. Finally, the efficiency of HDMTC was validated via real records from telecom company.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
