Profiling Subscribers According to Their Internet Usage Characteristics and Behaviors
Abstract
Providers (SP) are wishing to increase their Return of Investment (ROI)
by utilizing the data assets generated by tracking subscriber behaviors.
This results in the ability of applying personalized policies,
monitoring and controlling the service traffic to subscribers and
gaining more revenues through the usage of subscriber data with ad
networks. In this paper, a framework is developed to monitor and analyze
the Internet access of the subscribers of a regional SP in order to
categorize the subscribers into an interest category from The
Interactive Advertising Bureau (IAB) categories. The study employs the
categorization engine to build category vectors for all subscribers. The
simulation results show that once a subscriber has been classified into
a category the click rate for the same subscriber group can be improved
by correlating the interests of the subscribers with the advertisements.
Collections

DSpace@Karatay by Karatay University Institutional Repository is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License..