基于贝叶斯网络的网络品牌认知度评价方法

随着电子商务和网络经济的快速发展，网络品牌的不确定信息越来越多，给消费者的选择造成了很大的困扰。考虑到网购消费者普遍存在的重复购买属性以及网络品牌对消费期望的重要性，有必要考虑网络品牌对消费者购物期望的动态影响，探究一种科学有效的评价体系，完成对网络品牌认知度的评价。贝叶斯网络是获取不确定知识的有效方法。介绍贝叶斯网络的优势与特征，论证基于贝叶斯网络进行网络品牌分类的可行性。实验证明通过贝叶斯网络可以有效地对网络品牌进行分类，获取电子商务系统的所需信息，帮助用户进行网络品牌的选择和购买行为的决策。

Evaluation Method of Web Brands Recognition Based on Bayesian Network

With the rapid development of economic commerce and network economy,uncertainty knowledge of web brands becomes more prevalent,selection of consumer gets more and more difficult. Considering the repeat purchase properties for online shopping consumers and the importance of network brand to consumer expectations,so needing to consider the dynamic impact of network brand to consumers shopping expectations,explore a scientific and effective evaluation system,complete the online brand awareness of the evaluation. Bayes-ian network has proved to be an effective method obtaining uncertainty knowledge. Expound Bayesian network＆#39;s superiority and fea-tures,and illustrate the feasibility of web brands classification based on Bayesian network. The experiment result shows that through Bayesian network can classify the network brands effectively,gain more information from economic commerce system,and provide useful information for users.