基于决策树算法的IT专业就业模型

针对当前高校毕业生就业困难、人才培养方案不能适用社会需求等问题，对基于决策树算法的IT专业就业岗位和知识需求聚类模型进行分析。基于大数据技术，以IT专业学生就业及社会招聘信息为例，通过爬虫技术进行数据挖掘，并对数据进行爬取、清洗、存储等操作，获取包括岗位、工作地点、薪资、学历、工作经验、知识技能等属性的数据集合。根据特征集合及数据集合，采用ID3算法，以最大信息增益为目标，构建基于决策树算法的IT专业就业岗位和知识需求聚类模型。试验结果表明，该模型可促进IT人才资源科学管理与决策、解决高校IT专业毕业生就业难、提高高校IT人才培养水平。

Employment Model of IT Majors Based on Decision Tree Algorithm

In view of the current employment difficulties of college graduates and the fact that the talent training program can not meet the social needs, this paper analyzes the clustering model of IT professional employment posts and knowledge needs based on decision tree algorithm. Based on big data technology, taking the employment and social recruitment information of IT majors as an example, data mining is carried out through crawler technology, and the data is crawled, cleaned and stored to obtain data sets including job, work place, salary, education, work experience, knowledge and skills. According to the feature set and data set, the ID3 algorithm is used to construct the clustering model of IT professional employment and knowledge demand based on decision tree algorithm with the goal of maximizing information gain. The experimental results show that the model can promote the scientific management and decision-making of IT talent resources, solve the employment difficulties of IT graduates in colleges and universities, and improve the level of IT talent training in colleges and universities.