基于用户在CRM中的评论和以往使用的云用户下一步需求预测与估计

M. Darbandi, Saeed Haghgoo, Mahdi Hajiali, Alireza Khabir
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引用次数: 15

摘要

今天,信息技术和互联网已经成为人类生活中必不可少的因素。用户的需求水平在广泛增长,他们需要更通用的软件和硬件服务,他们还需要安全的过程和数据传输,动态访问,快速处理,并在他们的工作中节省更多的钱。在本文中,我们想提出一种新的方法来估计和预测下一个用户的需求,并在用户直接请求之前提供这些服务。我们的算法基于卡尔曼滤波,它使用用户的背景用法以及他们在CRM部分的建议来预测他们的下一个需求。通过提供用户的下一个需求,在他们的要求之前,我们可以提高客户满意度的水平,也可以通过推荐新的软件和应用程序赚取更多的钱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction and Estimation of Next Demands of Cloud Users based on their Comments in CRM and Previous usages
Today, IT technologies and the internet are become an essential factors in human life’s. The demands level of the users are growing extensively, they need more generic software and hardware services, also they need, security in their processes and data transfers, dynamic accessibility, swift processing and also saving more money in their works. In this paper, we want to present new method for estimating and predicting the next user demands, and provide those services before direct request of the users. Our algorithm is based on Kalman filtering, and it used background usages of the users along with their suggestions in CRM section to be able to predict their next needs. By providing the next needs of the users, before their request, we can improve the level of customer satisfaction and also earn more money via suggesting the new software and applications.
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