摘要
在线客户偏好对潜在客户的购买决策有重要影响。从这些客户偏好中发现产品的优点与缺点,有助产品制造商面向客户需求改进产品设计并制定更适合客户需求的商务战略。然而,问题的关键是如何在广泛分布的评论文本、评分等级等大量信息碎片中发现客户总体偏好。针对此问题,目前客户偏好相关研究文献尚未能提出有效解决方法。提出了一个称为面向大型群决策的自动一致性模型(简称ACMLGD),用于低成本、快速地自动计算面向在线客户偏好的大群客户偏好。实验结果表明,ACMLGD模型在大量客户偏好的客户意见中发现客户总体偏好的计算性能较好。为在线客户偏好的大群客户偏好自动集结建模及应用提供了一种新的实用方法。
Online consumer preferences have a strong influence on the decision-making processes of other potential buyers,in which uncover individually perceived strengths and weaknesses of the respective products,and so that can help the manufacturers improve their products design and make a better business strategy.The key question at this point is how to find customers'overall preferences in a wide range of information fragmentation,such as text,rating scale,and so on,and in which the literatures online consumer product reviews can be found,however the importance of each remains poorly understood.This paper develops a model,referred to an automatic consensus model for large group decision-making(ACMLGD),to automatically,quickly and cheaply estimate aggregate large group consumer preferences from online preferences.Experimental results are presented that prove that ACMLGD achieves the good performance.This paper provides a summary of practical implications to guide practitioners building models for estimate aggregate large group online consumer preferences.
作者
刘翔
LIU Xiang(School Management Shanghai University,Shanghai 200444,China)
出处
《计算技术与自动化》
2018年第4期55-66,共12页
Computing Technology and Automation
关键词
在线客户偏好
群决策
自动一致性
ERP
consumer preferences
group decision-making
automatic consensus
ERP
