Relevance feedback retrieval of time series data
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Load Regulation in Mobile Network with Planned Pricing Model based on User Behaviour
ICAS-ICNS '05 Proceedings of the Joint International Conference on Autonomic and Autonomous Systems and International Conference on Networking and Services
Mining changing customer segments in dynamic markets
Expert Systems with Applications: An International Journal
An intelligent market segmentation system using k-means and particle swarm optimization
Expert Systems with Applications: An International Journal
A time series representation model for accurate and fast similarity detection
Pattern Recognition
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Africa has witnessed an incredible boom in the number of mobile subscribers in mobile networks across Africa. With the rise in demand for capacity in cellular networks, greater pressure is being placed on the network planner. Customer segmentation has been traditionally used in cellular network planning to better understand customer demands and needs. By developing more accurate profiling methods, operators are in a better position to market products and forecast future demand more accurately. This work looks at the extraction of frequency patterns from traffic signals originating from a typical mobile network using multi-scale analysis. By studying the features extracted, the classification of typical subscribers in the network can be conducted more efficiently and with greater granularity.