In today’s society, with the support of information technology, the media is constantly developing in the direction of integration, which has a profound impact on all aspects of people’s social life. The brand of agricultural products is derived from the definition of brand, based on the differences of production areas, varieties and quality of characteristic agricultural products, and conveyed the information of characteristic agricultural products in the form of trademarks, certification marks, and product packaging. In order to solve the problems existing in the running process of brand promotion system of characteristic agricultural products, the concept of Internet of Things was introduced. The Internet of Things is a network that shows that objects and objects are connected with each other. Customers who use the Internet of Things can communicate and exchange information between any kind of goods. This paper focuses on the content of the improved K-means clustering model based on multibrand communication of agricultural products, expounds the analysis model and scope of agricultural product brand communication, applies the Internet of Things and related technologies to the brand promotion system of characteristic agricultural products, and simulates agricultural product brand communication by using big data fuzzy K-means clustering algorithm. Finally, the calculation of coincidence rate proves that the maximum distance between agricultural product brand communication influence and K-means clustering algorithm is consistent with the JC value of nodes, and the correct rate is as high as 90%. A communication mode that is more in line with the law of brand influence communication of agricultural products.

中文翻译：

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融合媒体时代基于大数据模糊K-Means聚类的农产品品牌传播影响力形成与扩散分析

当今社会，在信息技术的支持下，媒体不断向融合方向发展，深刻影响着人们社会生活的方方面面。农产品品牌源于品牌的定义，根据特色农产品产地、品种、品质的差异，以商标、认证标志、产品包装等形式传达特色农产品的信息。为解决特色农产品品牌推广体系运行过程中存在的问题，引入物联网概念。物联网是一个显示物体和物体相互连接的网络。使用物联网的客户可以在任何种类的商品之间进行信息交流和交换。本文重点介绍了基于农产品多品牌传播的改进K-means聚类模型的内容，阐述了农产品品牌传播的分析模型和范围，将物联网及相关技术应用于特色农产品品牌推广系统。产品，并利用大数据模糊K-means聚类算法模拟农产品品牌传播。最后通过重合率计算证明，农产品品牌传播影响力与K-means聚类算法的最大距离与节点的JC值一致，正确率高达90%。