摘要
随着电子商务的高速发展,网络购物越来越经济便捷,相比于传统的网下购物,更多的消费者选择网购,这就使得非理性购买行为大量涌现,研究网络消费者非理性行为势在必行。然而,学者们大多关注传统购物环境下的非理性购买行为,并且研究内容比较琐碎,缺乏系统的框架。考虑到很多消费者选择通过在线评论表达对购买行为的情感和观点,因此首先利用情感计算和文本挖掘技术,在充分挖掘语义资源的基础上,借助模糊数学理论构建模糊语义模型,同时,以内、外部诱导因素为前件,以消费者非理性购买程度作后件,建立了模糊推理模型;然后,针对消费者非理性购买行为和过程,通过protégé建立本体,梳理各个因素之间的联系,构建知识库;最后,利用Jess构建模糊推理事实库与规则库,通过Jess推理机获取消费者非理性购买程度。
With the rapid development of e-commerce,online shopping is becoming more and more economical and convenient.Compared with the traditional online shopping,more consumers choose online shopping,which leads to the emergence of a large number of irrational purchasing behaviors.Therefore,it is imperative to study the irrational behavior of online consumers However,most scholars pay attention to the irrational purchase behavior in the traditional shopping environment,and the research content is relatively trivial,lacking a systematic framework.Considering that many consumers choose to express their emotions and opinions on purchasing behavior through online reviews,we firstly use emotional computing and text mining technology to construct a fuzzy semantic model on the basis of fully mining semantic resources and using the theory of fuzzy mathematics.At the same time,taking the internal and external inducement factors as the antecedent and the irrational purchasing degree of consumers as the consequent,a fuzzy reasoning model is established.Then,aiming at consumers’irrational purchasing behavior and process,the knowledge base is constructed by sorting out the relationships among various factors.Finally,the fact base and rule base of fuzzy inference are constructed by Jess,and the consumers’irrational purchasing degree is obtained by Jess inference engine.
作者
于国欣
王泽瑞
闫伟
YU Guo-xin;WANG Ze-rui;YAN Wei(School of Computer Science and Engineering,Shandong Normal University,Jinan 250000,China)
出处
《计算机技术与发展》
2020年第2期80-87,共8页
Computer Technology and Development
基金
教育部留学回国基金
山东省高等学校科技计划项目(J15LN26)
山东省自然科学基金培养基金项目(ZR2018PF006)