农产品电子商务平台用户行为分析

发布时间：2018-10-08 12:22

【摘要】：伴随着信息技术与农业领域结合水平的不断提高,农产品电子商务平台企业相互的竞争变得越来越白热化,为了能保持老用户群同时不断发掘新用户群,则必须进一步提高自身平台服务水平。在这样的背景下,农产品电子商务平台企业必须重视自身所拥有的用户数据,并使用数据挖掘工具对用户行为进行分析,发现并深入了解用户的行为特点,并有针对性的提供相关农产品。本文首先对课题背景、目的以及现实作用进行了相关的描述,总结了当前农产品电商和数据挖掘在用户行为分析方面的研究进展,并阐述了本文各章之间的基本安排。第二章概括性地叙述了本文对数据挖掘和用户分析的基本理论的研究,随后介绍了数据挖掘技术的基本概念、步骤,接着介绍了聚类算法的一些基础知识,然后介绍了用户行为分析的概念和用户行为分析的常用方法并作出了比较。第三章为针对传统K-Means算法在农产品电商平台用户行为分析领域的运用进行改善,体现为对传统算法在最佳k值确定方面的不足做出改善,通过构造了加权距离函数,来实现最佳k值优化。在对最佳k值求解过程中,当函数值在k值取值区间内有最小时取得最佳k值,并给出了最佳k值的取值区间,提高了改进算法的速度,实验表明改进后的算法是有效的。第四章随后依据改进后的算法建立了农产品电子商务平台用户行为分析模型,细致地描述了改进K-Means算法在模型中的运用过程,其中对于数据的预处理的流程和采用的方法以及结果进行了说明。对某农产品电商平台用户行为分析的结果表明改进后算法在用户行为划分、协助平台企业拟制营销战略、针对用户不同需求提供不同农产品服务等方面是有可操作性的。本文第五章在建立的用户行为分析模型的基础上进行农产品电子商务平台用户行为分析系统设计,本章叙述了农产品电子商务平台用户行为分析系统的功能实现的总体框架,并说明了系统的主要功能,并对系统基本分析功能测试进行介绍,从而为系统进一步实现拓展功能奠定基础。最后对全文的研究工作进行了归纳总结,针对本文研究的不足从理论研究与实际应用两个方面提出了进一步研究的方向。
[Abstract]:With the development of the combination of information technology and agriculture, the competition between the enterprises of agricultural products e-commerce platform becomes more and more intense. In order to keep the old user group and explore the new user group, It is necessary to further improve their own platform service level. Under this background, the enterprises of agricultural products e-commerce platform must attach importance to the user data they own, and use data mining tools to analyze the user behavior, and find out and deeply understand the characteristics of user behavior. And to provide relevant agricultural products. Firstly, this paper describes the background, purpose and practical function of the subject, summarizes the current research progress of agricultural product e-commerce and data mining in user behavior analysis, and expounds the basic arrangement between the chapters of this paper. The second chapter describes the basic theory of data mining and user analysis, then introduces the basic concepts and steps of data mining, and then introduces some basic knowledge of clustering algorithm. Then, the concept of user behavior analysis and the common methods of user behavior analysis are introduced and compared. The third chapter is to improve the application of the traditional K-Means algorithm in the field of agricultural products e-commerce platform user behavior analysis, which is reflected in the improvement of the traditional algorithm in the determination of the best k value, through the construction of a weighted distance function. To achieve the best k value optimization. In the process of solving the best k value, the best k value is obtained when the function value is minimum in the value range of k value, and the interval of the best k value is given, which improves the speed of the improved algorithm. The experiment shows that the improved algorithm is effective. In chapter 4, based on the improved algorithm, the user behavior analysis model of agricultural products e-commerce platform is established, and the application process of improved K-Means algorithm in the model is described in detail. The flow of data preprocessing, the methods adopted and the results are explained. The results of user behavior analysis on an agricultural product e-commerce platform show that the improved algorithm is operable in the aspects of user behavior division, assisting the platform enterprise to draw up marketing strategy, and providing different agricultural products service according to the different needs of the users. In the fifth chapter, the user behavior analysis system of agricultural products e-commerce platform is designed based on the established user behavior analysis model. This chapter describes the overall framework of the function realization of the agricultural product e-commerce platform user behavior analysis system. The main functions of the system are explained, and the testing of the basic analysis function of the system is introduced, which lays a foundation for the further realization of the extended function of the system. Finally, the research work of this paper is summarized, and the direction of further research is put forward from two aspects of theoretical research and practical application.
【学位授予单位】：安徽农业大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F724.6;F323.7;TP311.13

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