發(fā)布時(shí)間：2018-10-08 12:22

【摘要】：伴隨著信息技術(shù)與農(nóng)業(yè)領(lǐng)域結(jié)合水平的不斷提高,農(nóng)產(chǎn)品電子商務(wù)平臺(tái)企業(yè)相互的競(jìng)爭(zhēng)變得越來(lái)越白熱化,為了能保持老用戶群同時(shí)不斷發(fā)掘新用戶群,則必須進(jìn)一步提高自身平臺(tái)服務(wù)水平。在這樣的背景下,農(nóng)產(chǎn)品電子商務(wù)平臺(tái)企業(yè)必須重視自身所擁有的用戶數(shù)據(jù),并使用數(shù)據(jù)挖掘工具對(duì)用戶行為進(jìn)行分析,發(fā)現(xiàn)并深入了解用戶的行為特點(diǎn),并有針對(duì)性的提供相關(guān)農(nóng)產(chǎn)品。本文首先對(duì)課題背景、目的以及現(xiàn)實(shí)作用進(jìn)行了相關(guān)的描述,總結(jié)了當(dāng)前農(nóng)產(chǎn)品電商和數(shù)據(jù)挖掘在用戶行為分析方面的研究進(jìn)展,并闡述了本文各章之間的基本安排。第二章概括性地?cái)⑹隽吮疚膶?duì)數(shù)據(jù)挖掘和用戶分析的基本理論的研究,隨后介紹了數(shù)據(jù)挖掘技術(shù)的基本概念、步驟,接著介紹了聚類算法的一些基礎(chǔ)知識(shí),然后介紹了用戶行為分析的概念和用戶行為分析的常用方法并作出了比較。第三章為針對(duì)傳統(tǒng)K-Means算法在農(nóng)產(chǎn)品電商平臺(tái)用戶行為分析領(lǐng)域的運(yùn)用進(jìn)行改善,體現(xiàn)為對(duì)傳統(tǒng)算法在最佳k值確定方面的不足做出改善,通過(guò)構(gòu)造了加權(quán)距離函數(shù),來(lái)實(shí)現(xiàn)最佳k值優(yōu)化。在對(duì)最佳k值求解過(guò)程中,當(dāng)函數(shù)值在k值取值區(qū)間內(nèi)有最小時(shí)取得最佳k值,并給出了最佳k值的取值區(qū)間,提高了改進(jìn)算法的速度,實(shí)驗(yàn)表明改進(jìn)后的算法是有效的。第四章隨后依據(jù)改進(jìn)后的算法建立了農(nóng)產(chǎn)品電子商務(wù)平臺(tái)用戶行為分析模型,細(xì)致地描述了改進(jìn)K-Means算法在模型中的運(yùn)用過(guò)程,其中對(duì)于數(shù)據(jù)的預(yù)處理的流程和采用的方法以及結(jié)果進(jìn)行了說(shuō)明。對(duì)某農(nóng)產(chǎn)品電商平臺(tái)用戶行為分析的結(jié)果表明改進(jìn)后算法在用戶行為劃分、協(xié)助平臺(tái)企業(yè)擬制營(yíng)銷戰(zhàn)略、針對(duì)用戶不同需求提供不同農(nóng)產(chǎn)品服務(wù)等方面是有可操作性的。本文第五章在建立的用戶行為分析模型的基礎(chǔ)上進(jìn)行農(nóng)產(chǎn)品電子商務(wù)平臺(tái)用戶行為分析系統(tǒng)設(shè)計(jì),本章敘述了農(nóng)產(chǎn)品電子商務(wù)平臺(tái)用戶行為分析系統(tǒng)的功能實(shí)現(xiàn)的總體框架,并說(shuō)明了系統(tǒng)的主要功能,并對(duì)系統(tǒng)基本分析功能測(cè)試進(jìn)行介紹,從而為系統(tǒng)進(jìn)一步實(shí)現(xiàn)拓展功能奠定基礎(chǔ)。最后對(duì)全文的研究工作進(jìn)行了歸納總結(jié),針對(duì)本文研究的不足從理論研究與實(shí)際應(yīng)用兩個(gè)方面提出了進(jìn)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.
【學(xué)位授予單位】：安徽農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：F724.6;F323.7;TP311.13

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