基于信息熵和贝叶斯方法的就业指导辅助决策技术

为了提高对大学生就业指导辅助决策的准确性和客观性，研究了基于数据挖掘技术进行就业指导辅助决策的技术及其实现的关键方法，根据学生基本信息和就业的历史记录，基于信息论的不确定性描述方法，分析了不同就业岗位上学生各类基本素质的重要程度，再根据属性重要程度提取影响就业的主要属性，在此基础上使用朴素贝叶斯算法进行就业预测分析,实践表明，按照文中提出的方法进行专业化就业指导，方法可行，结果符合实际情况．

RESEARCH ON INFORMATION ENTROPY AND BAYESIAN METHOD BASED ASSISTANCE DECISION MAKING TECHNOLOGY FOR EMPLOYMENT GUIDANCE

In order to improve the veracity and objectivity of decision making in employment guidance for graduates, key method and its implements for assistance decision making of employment guidance which based data mining are studied. With student basic information and their employment history record, factors associated with employment and its influence degree is analyzed based on uncertain information theory. The main factors are picked up for pre- dictable analysis based on theory of information entropy, using Bayesian method to predict employment. Experiment result indicates that construct a professional employment guidance system based on the method introduced in the paper is feasible, the decision conclusion conform to actual situation.