摘  要

目前，针对学生准确地获取高质量的就业招聘信息，企业便捷获取符合岗位需求的人才信息等问题，提出一种基于数据挖掘的大学生就业信息双向推荐系统方案，实现毕业生信息与企业招聘信息双向推荐的目的。该系统通过分析某城市若干高校历年毕业生就业管理工作中积累的大量就业数据信息，分别对毕业生信息和企业招聘信息进行聚类分析，同时对各毕业生与其成功就职的企业和岗位信息进行关联分析。

根据聚类规则对当前求职的毕业生和招聘企业分别进行分类，向各毕业生自动推荐其同类学生所关联的企业及岗位信息，同时向各企业自动推荐符合其岗位需求的毕业生信息.实验证明，该系统能够有效利用高校之间的就业信息资源共享机制，对各个高校的毕业生及企业岗位招聘信息进行准确聚类，实现毕业生和企业之间的双向推荐。

本次设计提取求职者的基本信息和求职意向等特征属性，提出了一种基于k-means的协同过滤推荐算法，该算法既考虑到求职者的兴趣偏好，有考虑到求职者与招聘公司之间的匹配程度，提高了推荐的准确率。通过Java Web技术设计和实现了求职招聘双向推荐系统软件，将推荐算法和招聘系统相结合。采用eclipse软件对以上算法进行编程，并实现进行窗体界面的设计。

关键词：数据挖掘；就业推荐；推荐管理；推荐算法；Java

Abstract

At present, in view of the students' accurate access to high-quality employment recruitment information and the convenient access of enterprises to talent information in line with the needs of the post, a two-way recommendation system scheme of employment information for college students based on data mining is put forward. To achieve the purpose of two-way recommendation of graduate information and enterprise recruitment information. By analyzing a large number of employment data information accumulated in the employment management of graduates in some colleges and universities in a certain city, the system carries on the cluster analysis to the graduate information and the enterprise recruitment information respectively. At the same time, the graduates and their successful employment of enterprises and post information correlation analysis.

According to the clustering rules, the graduates and recruitment enterprises are classified separately, and the enterprises and post information associated with their similar students are automatically recommended to each graduate. At the same time, enterprises are automatically recommended to meet their job needs of graduate information. The experiment shows that the system can effectively utilize the employment information resource sharing mechanism between colleges and universities, accurately cluster the recruitment information of graduates and enterprises in each university, and realize the two-way recommendation between graduates and enterprises.

By extracting the basic information and intention of job seekers, this design proposes a collaborative filtering recommendation algorithm based on k-means, which not only takes into account the interest preference of job seekers. Considering the matching degree between job seekers and recruitment companies, the accuracy of recommendation is improved. By Java Web technology design and implementation of job recruitment two-way recommendation system software, the recommendation algorithm and recruitment system are combined. eclipse software is used to program the above algorithm and to design the form interface.

Keywords: data mining; employment recommendation; recommendation management; recommendation algorithm; Java

目  录

摘  要

Abstract

1 引言

1.1选题背景及目的意义

1.1.1选题背景

1.1.2目的及意义

 1.2研究现状

1.3研究主要内容及结构

2 相关理论和开发工具

2.1 数据挖掘简述

2.2 相关数据挖掘算法概述

2.2.1关联规则

2.2.2 聚类算法

2.2.3 分类算法

2.3 文本挖掘概述

2.4 开发工具

3 系统分析

3.1可行性分析

3.1.1 技术可行性

3.1.2操作可行性

3.1.3 经济可行性

3.1.4 法律可行性

3.2系统流程设计

3.2.1 用户注册

3.2.2 用户登录

3.3性能需求

3.4运行需求

4 系统设计

4.1系统功能设计

4.1.1功能概述

4.1.2系统功能结构

4.2系统用例图

4.3数据库设计

4.3.1数据库设计原则

4.3.2数据库概念设计

4.3.3数据库E-R图设计

4.3.4数据库表设计

5 系统实现

5.1数据的采集与预处理

5.1.1数据的采集

5.1.2数据的预处理

5.2用户功能模块的实现

5.2.1 用户注册界面

5.2.2用户登录界面

5.2.3信息修改界面

5.2.4添加简历界面

5.2.5招聘详情界面

5.3管理员功能模块的实现

5.3.1管理员登录界面

5.3.2下载文档管理界面

5.3.3岗位管理界面

5.3.4会员管理界面

5.3.5企业管理界面

5.3.6企业分类管理界面

5.4企业功能模块的实现

5.4.1发布招聘信息界面

5.4.2招聘管理界面

6 系统测试

6.1功能测试

6.2可用性测试

6.3测试步骤

6.4测试结果分析

总  结

致  谢

参考文献