将神经聚类应用于企业业务改进

U. Marovac, A. Crnišanin, Mirslav D. Lutovac
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引用次数: 0

摘要

本文的目的是表明存储在公司数据仓库中的数据可以用于改善业务。运用数据挖掘、神经聚类等方法,研究了企业员工的年龄结构及其对企业的影响。这将有助于改善中小企业的就业政策。在分析的基础上,确定了零售业新人招聘的标准。本文以414个不同的零售行业为样本,通过为期三年(2004-2006)的半年度财务报告对这些行业的业务进行了跟踪调查,从销售者年龄结构的角度对销售依赖质量进行了分析。因此,我们得到具有适当属性的集群模板,这些属性可以描述销售的好坏,并具有负责该属性的供应商的适当年龄结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using neural clustering for business improvement companies
The aim of this paper is to show that the data stored in companies data warehouses can be used in order to improve business. By application of data mining method, neural clustering, we investigate age structure of employees and its influence on business companies. This would enable improvement in employment policy for small and medium-sized companies. The criteria while employing new people in retail trade is defined based on the analysis. The analysis of the quality of sales dependency from age structure of sellers is carried out on the sample of 414 different retail trades whose businesses have been followed up through semi-annual financial report for the period of three years (2004–2006). As a result we get cluster templates with the proper attributes which may describe good or bad sale and with proper age structure of the venders responsible for that.
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