摘要
在线商品质量可靠性控制是电子商务和网络中交易的前提,可以促进网络购物市场的健康良好发展。在线商品质量的可靠性控制,需要网络购物平台质量管控体系对商品关键质量特性进行排序。传统方法无法从这些海量在线商品中提取代表商品关键质量特性,导致对商品特性进行排序需要通过大量的计算,存在控制误差大、控制过程繁琐,耗时长的弊端。提出一种基于组合云服务流程网模型(CCSPNet)的在线商品质量可靠性控制算法。构建了在线商品质量属性多层矢量特征空间,在特征空间中进行在线商品的组合云服务流程模型构建CCSPNet模型,以CCSPNet模型为基础,对商品的质量数据进行K均值聚类分析,最后采用最小二乘拟合控制方法实现在线商品的优化控制。仿真结果表明,采用该方法能有效实现对质量可靠性控制,能实时准确地反映在线商品的质量性能,商品质量属性的特征匹配精度较高,性能优越,在电子商务优化管理系统设计中具有较好的应用价值。
A reliability control algorithm for online commodity quality is proposed based on combined cloud service process network model （CCSPNet）. The multilayer vector feature space of online commodity quality attributes is constructed. The cloud service process model of online commodity is combined in the feature space, and CCSPNet model is established. Based on the CCSPNet model, the quality data of the commodity is made K-mean clustering analysis. Finally, by using the least squares fitting control method, the optimization control of online commodity can be achieved. The simulation results show that the proposed method can effectively implement the reliability control of the quality, and accurately reflect the the quality performance of online commodity. The feature matching of quality attributes of commodity is of high precision, excellent performance, which has a good application value in design of the ecommerce optimization management system.
出处
《计算机仿真》
CSCD
北大核心
2016年第9期261-264,共4页
Computer Simulation
关键词
在线商品
电子商务
可靠性控制
Online commodities
E-commerce
Reliability control
