个性化电商网站系统的设计与实现

发布时间：2018-08-17 19:23

【摘要】：近年来,电子商务网站在全球的发展如火如荼,人们足不出户就能购买到想要的商品,网购已成为人们的一种消费习惯。美国的亚马逊、中国的淘宝等都是成功电商网站的案例。随着商品数量的增长,用户需要一种能为其提供个性化信息的工具,个性化推荐就能满足用户的这种需要。在这种背景下,笔者所在的实习公司为客户开发了这样一个个性化电商网站系统。本系统使用的开发语言为PHP,数据使用MySQL进行存储,用Redis做消息队列的缓存,采用了 B/S架构。本系统分为三个子系统,分别是网站管理子系统,日志采集子系统,推荐子系统。网站管理子系统分为前台商城和后台管理两个模块,前台商城主要为用户提供了登录/注册、浏览商品、收藏、加入购物车、下订单和个人中心管理等功能。系统后台分为商品管理、推荐管理、订单管理、折扣管理和用户管理等功能模块。日志采集子系统的主要功能包括日志采集功能、日志管理功能和日志统计功能。推荐子系统的主要功能包括获取用户行为数据、对推荐模型进行管理以及输出推荐结果,其中推荐模型应用了协同过滤的推荐算法为用户提供个性化推荐。本文对个性化电商网站系统进行了设计与实现。作者在项目过程中,参与了需求分析、概要设计、详细设计、代码编程、系统测试等环节。在需求分析阶段,多次与客户进行沟通交流,了解用户需求。通过需求分析,从用例的角度详细的阐述了每个用例的基本功能,以及系统的非功能性需求分析。在概要设计阶段,首先设计了系统架构,和各子系统的架构。然后根据需求分析将各子系统划分为几大模块,对各模块的功能进行了分析,并通过逻辑设计和概念设计对数据库进行分析。在详细设计里从代码层面对系统进行设计与实现,并通过类图描述类与类、方法与方法之间的调用关系。在实现阶段,使用公司常用的后台框架对项目进行了分层,前台使用了 Bootstrap,JQuery等框架。最后进行了系统测试,从功能和非功能两个方面对系统进行了全面的测试。最终系统得以在某公司上线应用。在上线一段时间后通过统计销售数据,验证了推荐算法大大提高了销量。此系统有良好的实用性,具有良好的可扩展性和安全性,通过个性化推荐为用户的网购带来了极大方便。
[Abstract]:In recent years, e-commerce websites in the global development is in full swing, people can buy what they want without leaving their homes, online shopping has become a consumption habit of people. Amazon in the United States, Taobao in China and other successful e-commerce sites are cases. With the increase of the number of products, users need a tool to provide them with personalized information, and personalized recommendation can meet the needs of users. In this context, the author's internship company for customers to develop such a personalized e-commerce website system. The development language of this system is PHP, the data is stored by MySQL, the message queue is cached by Redis, and the structure of B / S is adopted. The system is divided into three subsystems: website management subsystem, log collection subsystem and recommendation subsystem. The website management subsystem is divided into two modules: front shopping mall and background management. Front desk mall mainly provides users with the functions of login / register, browse merchandise, collect, join shopping cart, place orders and manage personal center. The system background is divided into commodity management, recommendation management, order management, discount management and user management and other functional modules. The main functions of log acquisition subsystem include log collection, log management and log statistics. The main functions of recommendation subsystem include acquiring user behavior data, managing recommendation model and outputting recommendation results. Recommendation model applies collaborative filtering recommendation algorithm to provide personalized recommendation for users. This paper designs and implements the personalized e-commerce website system. The author is involved in requirements analysis, outline design, detailed design, code programming, system testing and so on. In the requirement analysis phase, communicate with customers many times to understand the needs of users. Through requirement analysis, the basic function of each use case and the non-functional requirement analysis of the system are described in detail from the point of view of use case. In the outline design phase, the system architecture and the architecture of each subsystem are first designed. According to the requirement analysis, the subsystems are divided into several modules, the functions of each module are analyzed, and the database is analyzed through logical design and conceptual design. In the detailed design, the system is designed and implemented from the code level, and the calling relationship between class and class, method and method is described by class diagram. In the implementation phase, the project is layered with the company's usual background framework, and the foreground uses the framework such as Bootstrapan JQuery. Finally, the system is tested, from the functional and non-functional aspects of the overall test of the system. Finally, the system can be used online in a company. After going online for a period of time, through the statistics of sales data, the recommended algorithm greatly improved the sales volume. This system has good practicability, good expansibility and security.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.092

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