原文出自:https://blog.youkuaiyun.com/xiaokang123456kao/article/details/75006624
一好友推荐系统项目概述
1、项目介绍
该系统利用基于密度的新型聚类算法,对给定用户基于好友推荐。本系统的开发IDE采用myeclipse2014,使用maven构建项目,数据库选用Mysql,后台技术采用SpringMVC+Mybatis+Spring的架构,前端使用Easyui+Ajax的技术实现前后端的数据交互,算法的主要计算任务用Hadoop Mapreduce来完成。综合来说,本系统面临的主要挑战如下:
- 如何用MapReduce来实现聚类算法;
- 如何使用JavaWeb技术实现Hadoop任务的远程提交;
- 如何实现Hadoop任务的实时监控;
2、项目采用的用户数据源
本此项目的用户数据源样例如下:
<row Id="-1" Reputation="9" CreationDate="2010-07-28T16:38:27.683" DisplayName="Community" EmailHash="a007be5a61f6aa8f3e85ae2fc18dd66e" LastAccessDate="2010-07-28T16:38:27.683" Location="on the server farm" AboutMe="<p>Hi, I'm not really a person.</p>
<p>I'm a background process that helps keep this site clean!</p>
<p>I do things like</p>
<ul>
<li>Randomly poke old unanswered questions every hour so they get some attention</li>
<li>Own community questions and answers so nobody gets unnecessary reputation from them</li>
<li>Own downvotes on spam/evil posts that get permanently deleted
</ul>" Views="0" UpVotes="142" DownVotes="119" />
<row Id="2" Reputation="101" CreationDate="2010-07-28T17:09:21.300" DisplayName="Geoff Dalgas" EmailHash="b437f461b3fd27387c5d8ab47a293d35" LastAcc