基于多模型的移动电子商务推荐系统设计与实现

硕士学位论文

论文题目基于多模型的移动电子商务推荐系统

设计与实现

研究生姓名叶红霞

指导教师姓名刘纯平

专业名称计算机技术

研究方向电子商务

论文提交日期2013.04.20

基于多模型的移动电子商务推荐系统设计与实现中文摘要

基于多模型的移动电子商务推荐系统设计与实现

中文摘要

随着Internet的普及和应用，电子商务因为其成本低廉、便捷、快速、不受时间和空间的限制等优点已在全球流行。电子商务在为用户提供更多选择的同时，其结构也日益更加复杂。一方面，用户面对大量的商品信息，很难快速找到自己真正需要的商品；另一方面，商家也无法与消费者面对面的交流。个性化的电子商务推荐系统能根据用户行为特征为用户提供一对一的服务，快速帮助用户找到所需的商品，从而顺利完成购物过程。商家通过推荐系统能提高电子商务系统销售能力，保持与客户的联系，提高用户忠诚度和满意度。

本文通过对当前B2C网站的电子商务个性化推荐系统分析，提出一种B2C模式下的多模型推荐系统（MMRS）的设计及实现，该系统通过对用户购物历史记录、Wap元数据以及用户注册信息处理，运用关联、聚类的方法，最后给出商品的推荐结果。这种对不同用户的多模型的推荐方案，即使新老用户由于信息的不同，都能够产生有效的推荐，并能够对新产品产生推荐。文中在推荐算法上做了一定改良，最后利用同组同学的Wap电子商务网站测试数据，对MMRS系统进行验证，发现改良后的算法能收到比较好的效果。

关键词：数据挖掘，电子商务，推荐系统，关联分析，交叉销售

作者：叶红霞

指导老师：刘纯平（副教授）

Abstract Design and Accomplishment of Mobile e-Commerence Recommendation System based on Multi-Model Design and Accomplishment of Mobile e-Commerence Recommendation System based on Multi-Model

Abstract

With the fast development of Internet，E-commerce has become more and more popular all over the world. Business hence could overcome spatial and temporal barriers and are now capable of serving customers electronically and intelligently. However, the exponentially increasing amount of data and information along with the rapid expansion of business web sites and information systems make business hard to manage. On the other hand，it is also difficult for customers to find the products they want. For these reasons，the personalized recommendation system arises at the right moment, which provides customers one-to-one service based on their past behavior and reference from other users with similar preferences. Many companies nowadays are using this system to retain existing customers and attract new ones.

The article proposes a new multi-models recommendation system's (MMRS) design and realization based on the current B2C website electronic commerce personalization recommendation system's analysis. The system deals with purchasing history, Wap data and user's registration information, uses the associate rule and cluster method, recommending the result in the way of commodities. The plan can give effective recommendation and new kinds of commodities to new and old users according to the different information. There is some improvement in recommending calculate and testing it with some data from a Wap site by my partner, and carrying on a verification to the MMRS system, and at the end we can find the improved calculate can receive good effect.

Key Word: Data mining，Electronic Commerce，Recommendation Systems，Cross-sell，Relationship Analysis

Written by:Hongxia Y e

Supervised by:Chunping Liu