利用数据挖掘技术的电子图书商城设计与实现
发布时间：2018-10-19 15:17
【摘要】：随着互联网技术的高速发展,电子商务产业正逐步占领着传统产业的市场份额,越来越多的传统行业开始转变或发展电商业务,2014年,也是电子商务发展最为关键的一年,阿里巴巴赴美上市不仅成就了马云中国首富的地位,更让全世界看到了这个全球最大的移动电商公司是来自中国。马云曾宣称21世纪阿里要作一个伟大的数据公司,这让大家想到阿里巴巴的大数据有多么可怕。如何将这些数据转换成有用的信息,为公司创造更多的潜在利润,数据挖掘技术在其中起止举足轻重的作用,它可以有效地帮助企业分析网络中的大量数据,发现其隐藏的规律性,筛选出有效信息,进而指导企业调整营销策略,给客户提供更加个性化的高效率服务[1]。本文首先对国内外电子商务现状进行分析,了解和学习目前流行的电子商务网站框架,分析其功能和结构设计,并就如何能够增加用户体验度做了进一步的研究,完成本系统的总体设计,包括整个电子图书商城系统的图书、订单、顾客信息管理,用户登录注册、查询书目、购物车管理、图书评论等功能。然后着重研究各大电子商务网站中的个性化推荐功能,从分析和研究国内外流行电子商务网站,从而实现本系统的个性化推荐功能[2]。本系统的个性化推荐功能围绕数据挖掘的两个分析模型开始,一个是对客户数据预处理模型,另一个是基于遗传算法的关联规则算法模型。数据挖掘技术在电子商务中的应用可以将电子图书商城的浏览者转变为购买者。通过系统中的个性化推荐功能,分析浏览者的上网轨迹、兴趣爱好,从而向其推荐适合自己的商品,为商家提供利润。当用户要结账时,可以根据已经购买的商品,推荐同一类型的打折商品或热门商品,加强原有的产品或服务,从而提高商品之间的关联能力。个性化的服务使网站与客户之间建立起了一条牢固的纽带,使网站成为客户在日常生活中必不可少的一部分,通过使用个性化推荐功能,可以轻松的得到客户想要的商品,将顾客更多地吸引到自己的网站[3],从而提高客户对电子商务网站的忠诚度。
[Abstract]:With the rapid development of Internet technology, e-commerce industry is gradually occupying the market share of traditional industries. More and more traditional industries begin to change or develop e-commerce business. 2014 is also the most critical year for the development of e-commerce. Alibaba's listing in the United States not only made Ma the richest man in China, but also showed the world that the world's largest mobile e-commerce company is from China. Ma's claim that Ali will be a great data company in the 21st century reminds us of Alibaba's big data. How to convert these data into useful information and create more potential profits for companies, data mining technology plays an important role in it, it can effectively help enterprises to analyze a large amount of data in the network. Find its hidden regularity, screen out the effective information, then guide the enterprise to adjust the marketing strategy, and provide more personalized and high efficiency service to the customer [1]. In this paper, we first analyze the current situation of e-commerce at home and abroad, understand and study the current popular e-commerce website framework, analyze its function and structure design, and do further research on how to increase the degree of user experience. Complete the overall design of the system, including the entire e-book mall system of books, orders, customer information management, user login registration, query bibliography, shopping cart management, book review and other functions. Then, the individualized recommendation function of each E-commerce website is studied emphatically, and the individualized recommendation function of this system is realized by analyzing and studying the popular E-commerce websites at home and abroad. The personalized recommendation function of this system begins with two analysis models of data mining, one is the pre-processing model of customer data, the other is the association rule algorithm model based on genetic algorithm. The application of data mining technology in e-commerce can change the visitors of e-book mall into buyers. Through the personalized recommendation function in the system, the article analyzes the online track and interests of the visitors, so as to recommend their own products and provide profit for the merchants. When users want to check out, they can recommend the same type of discounted goods or hot goods according to the goods they have purchased, so as to strengthen the original products or services, so as to improve the ability of connection between goods. The personalized service has established a strong bond between the website and the customer, making the website become an indispensable part of the customer's daily life. Through the use of personalized recommendation function, you can easily get the goods that the customer wants. Attract more customers to their own websites [3], thus increasing customer loyalty to e-commerce sites.
【学位授予单位】：北京工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP311.13;TP393.092
，
本文编号：2281522
[Abstract]:With the rapid development of Internet technology, e-commerce industry is gradually occupying the market share of traditional industries. More and more traditional industries begin to change or develop e-commerce business. 2014 is also the most critical year for the development of e-commerce. Alibaba's listing in the United States not only made Ma the richest man in China, but also showed the world that the world's largest mobile e-commerce company is from China. Ma's claim that Ali will be a great data company in the 21st century reminds us of Alibaba's big data. How to convert these data into useful information and create more potential profits for companies, data mining technology plays an important role in it, it can effectively help enterprises to analyze a large amount of data in the network. Find its hidden regularity, screen out the effective information, then guide the enterprise to adjust the marketing strategy, and provide more personalized and high efficiency service to the customer [1]. In this paper, we first analyze the current situation of e-commerce at home and abroad, understand and study the current popular e-commerce website framework, analyze its function and structure design, and do further research on how to increase the degree of user experience. Complete the overall design of the system, including the entire e-book mall system of books, orders, customer information management, user login registration, query bibliography, shopping cart management, book review and other functions. Then, the individualized recommendation function of each E-commerce website is studied emphatically, and the individualized recommendation function of this system is realized by analyzing and studying the popular E-commerce websites at home and abroad. The personalized recommendation function of this system begins with two analysis models of data mining, one is the pre-processing model of customer data, the other is the association rule algorithm model based on genetic algorithm. The application of data mining technology in e-commerce can change the visitors of e-book mall into buyers. Through the personalized recommendation function in the system, the article analyzes the online track and interests of the visitors, so as to recommend their own products and provide profit for the merchants. When users want to check out, they can recommend the same type of discounted goods or hot goods according to the goods they have purchased, so as to strengthen the original products or services, so as to improve the ability of connection between goods. The personalized service has established a strong bond between the website and the customer, making the website become an indispensable part of the customer's daily life. Through the use of personalized recommendation function, you can easily get the goods that the customer wants. Attract more customers to their own websites [3], thus increasing customer loyalty to e-commerce sites.
【学位授予单位】：北京工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP311.13;TP393.092
，
本文编号：2281522
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