基于大数据技术的信息安全专业校企合作人才推荐方法

Recommendation Method for School Enterprise Cooperation Talents of Information Security Specialty Based on Big Data Technology

当前人才推荐方法在进行数据特征转换时没有将单独编码简化,导致计算时存在误差,所以对人才的回招程度较低。针对上述问题,提出了基于大数据技术的信息安全专业校企合作人才推荐方法。利用大数据技术的分布式采集方法收集人才信息,并使用Embedding神经网络技术对收集到的信息进行单独编码的简化,从而完成数据的特征转化。将转化后的特征数据作为人才推荐生成模型的输入,使用模型重叠模式加载大数据神经网络模型,完成人才推荐方法的设计。在实验中,将采集到的数据分为加载数据集和算法实验数据集进行验证。经实验结果分析证明,采用提出的基于大数据技术的信息安全专业校企合作人才推荐方法的F1-score数值较高,可以达到0.873。此方法可以有效提高推荐人才的精准度,对改善信息安全专业校企合作的人才缺少状况有一定的现实意义。

The current talent recommendation method does not simplify the separate code when converting data characteristics,resulting in errors in the calculation, so the recruitment of talents is low. Therefore, a recommendation method for school enterprise cooperation talents of information security specialty based on big data technology is proposed. The distributed collection method of big data technology is used to collect talent information, and the collected information is simplified by separately coding through Embedding neural network technology, so as to complete the feature transformation of data. The transformed feature data is used as the input of talent recommendation generation model, and the big data neural network model is loaded using the model overlap mode to complete the design of talent recommendation method. In the experiment, the collected data is divided into the loading data set and the algorithm experiment data set, and the proposed method is verified. The analysis of the experimental results shows that the F1 score value of the proposed recommendation method for school enterprise cooperative talents of information security major based on big data technology is high, which can reach 0.873. This method can effectively improve the accuracy of recommended talents, and has a certain practical significance to improve the lack of talents for school enterprise cooperation in information security.