社交网络的数据挖掘.doc

闽江学院 本科毕业论文(设计) 题 目 社交网络的数据挖掘 学 号 系 别 软件学院 年 级 13级 专 业 软件工程 指导教师 职 称 讲师 完成日期 2015.4.23 闽江学院毕业论文（设计）诚信声明书 本人郑重声明： 声明人（签名）： 年 月 日 With the development of information technology and economy more and more rapidly, social networking has become an indispensable part of peoples lives, the exchange of peoples daily life has a lot of big part is through the network, social networking sites to communicate, so the social network has become a new expensive network, researchers have begun to study how to get better in social the website information is becoming popular, people have begun to study the social networking site data mining technology. In order to obtain useful information in social networking sites, so data mining in a large number of social networking sites. The purpose of data mining and data warehouse is to in large amounts of data analysis has become a popular information. The fundamental success of social networking sites for data mining is data mining technology and data warehouse of large amounts of data processing results effectively, but also determines the social networking site for data mining is the key of success, the accurate information is to ensure the implementation of data mining. The bean, Facebook, Twitter and other mainstream social media sites the user data acquisition, calculation and statistical analysis, and focuses on the analysis of node degree (i.e. the number of a node and other nodes connected), distribution of node degree correlation. Key words: Data mining; Social network; Node degree; Correlation analysis 目录 第一章绪论 5 1.1 研究背景和意义 5 1.2 国内外研究现状 5 1.3论文的结构安排和研究内容 6 1.3.1三种权限 6 1.3.2主要研究内容包括： 6 1.3.3结构安排如下： 6 第二章数据挖掘技术 7 2.1数据挖掘论述 7 2.2 数据挖掘技术 7 2.2.1典型数据挖掘系统 7 2.2.2数据挖掘概念 8 2.2.3数据挖掘模式 8 第三章数据挖掘技术研究 9 3.1 目标数据 9 3.2 数据的关联分析 9 3.2.1关联分析的概念 9 3.2.2 Apriori算法 9 3.2.3事件驱动 10 第四章模型建立和数据分析 11 11