基于R软件的关联规则算法在购物篮分析中的应用

发布时间：2018-04-19 11:12

本文选题：数据挖掘 + 关联规则　；参考：《华中师范大学》2017年硕士论文

【摘要】：随着计算机科学技术的不断向前发展,人类的生活变得越来越智能化,人类正进入一个全新的信息化、科技化的时代。在信息化的今天,数据的获取成为一件相对简单的事情。其原因在于数字化技术的广泛应用;此外,互联网的普及应用,网民的数量越来越多,从而给人类带来了海量的信息,也为人类的研究和探索提拱了便利。数据挖掘是从数据中挖掘出有价值的、人类所不知道的信息,而关联规则算法挖掘就是其研究和探索的一个重要领域。本文简单介绍了关联规则算法的一些基本概念,并探讨分析了其在“购物篮分析”中的应用。国内外研究者研究了数据挖掘与“购物篮分析”在超市中的关系,并研究一系列问题。如采取怎样的销售策略、怎样去销售产品以及在超市中如何摆放产品等进行了大量的研究。在上述的背景下。本文主要是希望对关联规则算法进行深入的研究,及其在“购物篮分析”中的实现问题,以及把分析出的结果如何应用到实际决策中。本文主要进行了以下探讨:(1)对数据挖掘技术的项目背景及国内外现状做了简单介绍,探讨了其应用领域的广泛性、效益性,并提出该技术在超市中的作用。(2)接下来,简单介绍了数据挖掘的一些相关概念,及其在理论上探讨数据挖掘的任务。在此基础上,介绍了实际工作中,其挖掘的一般性流程。(3)接着,对关联规则算法进行了全面的分析,特别是对经典的Apirori算法进行深彻的剖析和研究。并就其经典算法进行举例分析。(4)关联规则应用性研究。就是将关联规则算法与“购物篮分析”的实际问题相结合。首先,对“购物篮分析”的基本理论和方法进行了简单介绍,用R软件进行频繁项集的生成,再根据频繁项集生成关联规则,并将关联规则结果可视化,并利用商品之间互相的联系,实现了商品摆放次序的优化。对分析的过程和结果进行了阐述和说明,从而为超市在决策时提拱了更多理论支持。
[Abstract]:With the continuous development of computer science and technology, human life has become more and more intelligent, and mankind is entering a new era of information, science and technology.In the information of today, the acquisition of data has become a relatively simple thing.The reason lies in the wide application of digital technology; in addition, with the popularization of the Internet, the number of Internet users is increasing, which brings massive information to human beings, and also facilitates the research and exploration of human beings.Data mining is a kind of valuable and unknown information from data, and association rule mining is an important field of research and exploration.This paper briefly introduces some basic concepts of association rule algorithm and discusses its application in shopping basket analysis.Researchers at home and abroad have studied the relationship between data mining and shopping basket analysis in supermarkets and a series of problems.Such as how to take the sales strategy, how to sell products and how to put products in the supermarket and so on a lot of research.Against the above background.In this paper, we hope to study the association rules algorithm and its implementation in "shopping basket analysis", as well as how to apply the analysis results to the actual decision-making.This paper mainly discusses the project background of data mining technology and the present situation at home and abroad, discusses its wide application and benefit, and puts forward the function of this technology in supermarket.This paper briefly introduces some related concepts of data mining, and discusses the task of data mining in theory.On this basis, the general process of mining is introduced. Then, the association rule algorithm is analyzed comprehensively, especially the classical Apirori algorithm.An example is given to analyze the application of association rules.It is to combine the association rule algorithm with the practical problem of shopping basket analysis.Firstly, the basic theory and method of "shopping basket analysis" are introduced briefly. The frequent itemsets are generated by R software, then association rules are generated according to frequent itemsets, and the results of association rules are visualized.By using the relationship between commodities, the order of commodity placement is optimized.The process and results of the analysis are expounded and explained, thus providing more theoretical support for supermarket decision-making.
【学位授予单位】：华中师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.13;F274

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