Timely and personalized services using mobile cellular data

Abstract

The 21st-century data-driven economy is rapidly evolving and large companies like Telecom operators are forced to adapt their business. They are shifting their focus from traditional but exhausted connectivity provider market towards a more services based market. Here competition is high, and other stakeholders are trying to monopolize the data-driven world of personalized services. But, Telecom operators are the custodians of Call Detail Records (CDRs), which captures mobility activities and social ties of a large number of users. Recently researchers observed that CDRs are the most valuable form of data to perform user-centric analysis, especially when related to mobility and habits.In this paper, we demonstrate that CDRs can be used to provide personalized and timely services. Specifically, we show that it can be used to provide a recommendation service, one of the most popular personalized services. In addition, we demonstrate the advantage of leveraging human behavior characteristics for such services. Our REGULA recommendation algorithm, that builds on the analysis of human habits, outperforms the state of the art recommendation algorithms. We advocate that Telecom operators can leverage CDRs to provide personalized services in a data-driven world and can significantly alter the landscape of timely and personalized services.