构建基于云的回归模型来预测商业消息传递活动的点击率

Alexandros Deligiannis, Charalampos Argyriou, D. Kourtesis
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引用次数: 3

摘要

本文的研究目标是描述一种创新的方法,通过估计将与消息交互的消息接收者的百分比来预测业务消息传递活动的影响。其动机是帮助企业营销人员解决估算潜在消息传递活动的投资回报的问题。该解决方案依赖于大规模业务数据的处理,考虑到最先进的预测算法、GDPR合规性要求以及数据安全性和可用性提高的挑战。在本文中,我们讨论了能够实现这一目标的系统核心功能组件的设计,其中包括云计算环境中的预测分析,数据挖掘和机器学习技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building a Cloud-based Regression Model to Predict Click-through Rate in Business Messaging Campaigns
The goal of the research presented here is to describe an innovative approach to predicting the impact of a business messaging campaign, by estimating the percentage of message recipients who will engage with a message. The motivation is to facilitate business marketers to address the problem of estimating the return on investment coming from a potential messaging campaign. The presented solution relies on the processing of large scale business data, taking into account state-of-the-art predictive algorithms, GDPR compliance requirements, and the challenge of increased data security and availability. In this paper we discuss the design of the core functional components of a system that could make this possible, which encompasses predictive analytics, data mining and machine learning technologies in a cloud computing environment.
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