Consumer Behavior of Multimedia Image Data Fusion Algorithm in E-Commerce Environment

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Abstract

With the rise of the Internet, e-commerce has penetrated into all aspects of people’s lives. This paper classifies the consumers in e-commerce environment, constructs the feature set of social commerce customer portrait, and then uses multimedia image data fusion algorithm to extract the salient features of customers, and then paints the customer portrait in e-commerce environment. Based on the establishment of the feature database of the customer portrait, through the construction and reconstruction of the original data set, the behavior characteristics of the customer are analyzed comprehensively. This paper establishes a customer portrait model that can handle both categories and continuity at the same time to get the features that affect customers, and gives the characteristic trend of customer consumption. In terms of shopping ratings, customers are clearly choosing 3.5 and 4-star merchants, with 55% choosing 3.5 to 5 stars. This paper can improve customers’ trust in merchants, improve user stickiness, and maintain the relationship between consumers and merchants, which is conducive to the spread of Internet word-of-mouth.
电子商务环境下多媒体图像数据融合算法的消费者行为研究
随着互联网的兴起,电子商务已经渗透到人们生活的方方面面。本文对电子商务环境下的消费者进行分类,构建社交电子商务客户画像特征集,然后利用多媒体图像数据融合算法提取客户的显著特征,绘制电子商务环境下的客户画像。在建立客户画像特征数据库的基础上,通过对原始数据集的构建和重构,全面分析客户的行为特征。本文建立了同时处理品类和连续性的顾客画像模型,得到了影响顾客的特征,并给出了顾客消费的特征趋势。在购物评分方面,消费者明显选择3.5星和4星的商家,55%的人选择3.5星到5星。本文可以提高顾客对商家的信任度,提高用户粘性,维护消费者与商家之间的关系,有利于网络口碑的传播。
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