Ranking-based business information processing: applications to business solutions and eCommerce systems

Mao Chen, J. Sairamesh
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引用次数: 2

Abstract

Extracting crucial information in high volume business data efficiently are critical for enterprises to make timely business decisions and adapt accordingly. This paper proposes a novel ranking-based system that applies knowledge models and utility functions. In a case study for monitoring and analyzing automotive failures in aftermarket services, we shed a light on our ranking mechanism that combines objective business metrics and "subjective" domain knowledge. Our experiments using real-world data demonstrate that our methodology is capable of capturing macro view about business performance issues from a small but important fraction of information.
基于排名的商业信息处理:应用于商业解决方案和电子商务系统
高效地从海量业务数据中提取关键信息,是企业及时做出业务决策并进行相应调整的关键。本文提出了一种应用知识模型和效用函数的基于排序的系统。在一个监测和分析售后市场服务中的汽车故障的案例研究中,我们阐明了结合客观业务指标和“主观”领域知识的排名机制。我们使用真实数据进行的实验表明,我们的方法能够从一小部分但重要的信息中获取有关业务绩效问题的宏观视图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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