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User Modeling for Telecommunication Applications: Experiences and Practical Implications

机译:电信应用的用户建模:经验和实际影响

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Telecommunication applications based on user modeling focus on extracting customer behavior and preferences from the information implicitly included in Call Detail Record (CDR) datasets. Even though there are many different application areas (fraud detection, viral and targeted marketing, churn prediction, etc.) they all share a common data source (CDRs) and a common set of features for modeling the user. In this paper we present our experience with different applications areas in generating user models from massive real datasets of both mobile phone and landline subscriber activity. We present the analysis of a dataset containing the traces of 50,000 mobile phone users and 50,000 landline users from the same geographical area for a period of six months and compare the different behaviors when using landlines and mobile phones and the implications that such differences have for each application. Our results indicate that user models for a variety of applications can be generated efficiently and in a homogeneous way using an architecture based on distributed computing and that there are numerous differences between mobile phone and landline users that have relevant practical implications.
机译:基于用户建模的电信应用于从呼叫详细记录(CDR)数据集中隐式包括的信息中提取客户行为和偏好。尽管存在许多不同的应用领域(欺诈检测,病毒和有针对性的营销,流失预测等),它们都共享一个常见的数据源(CDR)和用于建模用户的常见功能集。在本文中,我们在从移动电话和固定电话订户活动的大规模实时数据集中生成用户模型时,我们向不同应用领域展示了我们的经验。我们介绍了一个数据集,其中包含了50,000个手机用户的痕迹和来自同一个地理区域的50,000个固定电话的六个月,并在使用固定电话和手机时比较不同的行为以及这些差异对每个差异的影响应用。我们的结果表明,各种应用的用户模型可以使用基于分布式计算的架构有效地,并以同一性方式生成,并且移动电话与具有相关实际意义的固定用户之间存在许多差异。

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