摘 要
本课题按设计先实现一个普通的在线服装销售平台，然后在该平台的基础上结合数据挖掘算法实现对客户的喜好进行建模分析，做到个性化推荐，得到“智能商城”的效果。
针对服装的销售，智能商城有助于企业或商家收集用户的个人信息，地理位置等信息。并通过购买记录，浏览记录来建立用户的喜好模型,调整商品的显示和推荐消息的推送,以提升用户的体验和满意程度。
对于卖家，智能商城提供对商品的销售情况进行统计，从而简化了传统的通过手工完成的繁琐流程，有利于卖家能及时准确地制定销售计划以及决策方案。允许卖家进行商品增删以及商品信息的更新，以满足基本的销售需求。另外卖家可以实时更新用户的喜好模型，以便更加准确地做出个性化推荐。
本服装销售平台是在Windows 7 环境下开发的。JDK版本为1.8，开发工具主要是Myeclipse。数据库采用SQL Server2008，采用开源的Tomcat作为WEB服务器。
Design and Implementation of Clothing Sales Platform Based on Data Mining Algorithm
Author: Tu Shunlin Specialty: Computer Science and technology Tutor: Liu Li
Abstract
A general online clothing sales platform was implemented according to the design.Combine data mining algorithms based on the platform to realize modeling analysis of customer preferences, which will ensure personalized recommendation to reach the "smart mall" effect.
For the sale of clothing, smart mall will help businesses to collect the user's personal information, geographic location and other information. And through the purchase of records, browse records to establish the user's preferences model,adjust the display of goods and recommended news to push,which will enhance the user experience and satisfaction.
For sellers,smart mall will help to provide the statistics of goods, which simplifies the traditional complex manual process and conducive to the seller to make accurate sales plan and decision making program timely. In addition to this,smart mall allow the seller to delete or update the information of products, to meet the basic needs of the sales. Besides, the seller was allowed to update the user's preferences model in real time, in order to make personalized recommendation more accurately.
Keywords： Data Mining Algorithm Clothing sales
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