利用数据挖掘技术提高半导体行业计费系统的性能

Yeh-Cheng Chen, Yu-Teng Chang, Y-S Kan, R. Chen, S. F. Wu
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引用次数: 3

摘要

新的计费方式主要是将数据仓库的概念与相关计费数据集成;此外,还利用关联规则挖掘的方法对计费数量模式进行了梳理,进而计算出计费数量。此外,采用数据挖掘中的决策树算法找出单位计费价格。因此,采用数据仓库和数据挖掘的方法构建了新的计费方法。本研究的重点是改进现有计费系统的运行,建立计费数量和计费价格的新功能。至于这两个新功能的好处,它不仅可以引入客户的计费系统,而且还可以在快速设置中提升效率;特别是对于内部已经拥有计费系统但尚未实施的企业。此外,它还可以减少收入差异,缩短开票流程,加快出口操作,提高出口效率,并提供收入数据集成到执行数据系统(EIS),决策支持系统(DSS)和商业智能系统(BIS),让企业及时做出正确的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using data mining technique to improve billing system performance in semiconductor industry
The new billing approaches are manly to apply the integrated concept of data warehouse with relevant billing data; in addition, use the methods of mining association rule to sort out the Billing Quantities Pattern and then figure out the billing quantities. Moreover, employ the Decision Tree algorithm of data mining to find out the unit billing price. As a result, the new billing approach is made of the methods of data warehouse and date mining. This study is mainly focused on improving the operation of current billing system to establish the new functionality of the Billing quantities and Billing price. As for the benefit of these two new functions, it is not only able to lead into clients' billing systems, but it is also capable of upgrading the efficiency in rapid setup; especially for the enterprises that already possessed billing system internally but not yet implemented. In addition, it can also reduce the difference in revenue, shorten the process of issuing invoice, speed up the export operation, increase the export efficiency and provide the revenue data for integrating into the Executive Data System (EIS), Decision Support System (DSS) and Business Intelligent System (BIS) to allow enterprises making the right decisions promptly.
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