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Proposed Ranking for Point of Sales Using Data Mining for Telecom Operators

机译:电信运营商使用数据挖掘的销售点拟议排名

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This study helps telecom companies in making decisions that optimize its sales points to reduce costs, alsoto identify profitable customers and churn ones. This study builds two research models; physical model forcontinuous mining of database where ever it resides i.e., as we have On Line Analytic Processing (OLAP)we must have On Line Data Mining (OLDM), and logical model using Technology Acceptance Model.Previous Studies showed that using basic information of customers, call details and customer servicerelated data, a model can effectively achieve accurate prediction data.This research gives a new definition and classification for telecommunication services from the datamining point of view. Then this research proposed a formula for total rank a shop and each term of thisformula gives a sub rank. The proposed example shows that even a shop with lower numbers of populationand visitors, it still has higher rank.This research suggested that telecom operators has to concentrate more on their e-shopping and epaymentas it is more cost effective and use data from shops for marketing issues. Some assumptions madein this study need to be validated using surveys, also proposed ranking should be applied on live database.
机译:这项研究可帮助电信公司制定优化销售点的决策,以降低成本,并确定可盈利的客户和流失的客户。本研究建立了两个研究模型;用于连续挖掘数据库的物理模型(例如,拥有在线分析处理(OLAP),我们必须具有在线数据挖掘(OLDM))和使用技术接受模型的逻辑模型。先前的研究表明,使用客户的基本信息,呼叫详细信息和与客户服务相关的数据,模型可以有效地获得准确的预测数据。本研究从数据挖掘的角度为电信服务提供了新的定义和分类。然后,本研究提出了商店总等级的公式,该公式的每个术语给出了一个子等级。所建议的示例表明,即使是一家人口和访客人数较少的商店,其排名仍然较高。该研究表明,电信运营商必须更加专注于其电子购物和电子支付,因为它更具成本效益,并使用商店中的数据进行营销问题。本研究中做出的一些假设需要使用调查进行验证,建议的排名也应应用于实时数据库。

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