基于卷积神经网络的高校就业教育个性化学习资源检索方法研究

Study on Personalized Learning Resource Search Method in College Employment Education Based on Convolutional Neural Network

常规就业教育个性化学习资源检索方法在关键词检索过程中出现漏检、错检的问题,影响了最终的资源检索结果。因此,设计了基于卷积神经网络的高校就业教育个性化学习资源检索方法。文章建立高校就业教育个性化学习资源检索索引,在学习资源中建立全文倒排索引,从不同的区域获取资源,从而确保资源检索的全面性。基于卷积神经网络检索个性化学习资源拼音结构,将重要资源的分词后中文分词转化为对应的拼音。文章将每个拼音映射一个汉字,从而获取学习资源的完整信息。采用对比实验,验证了该方法的学习资源检索效果更佳,能够应用于实际生活。

The conventional retrieval method of personalized learning resources in employment education are prone to issues of the problems of missing and wrong checking in the process of keywords retrieval,which affects the final resource retrieval results.Therefore,a personalized learning resource retrieval method for college employment education based on convolutional neural network is designed.Establish a personalized learning resource retrieval index for employment education in colleges and universities,and establish a full-text inverted index in the learning resources to obtain resources from different regions,so as to ensure the comprehensiveness of resource retrieval.Based on the convolutional neural network,we retrieve the pinyin structure of personalized learning resources,and the Chinese words of important resources are transformed into the corresponding pinyin,and each pinyin maps one Chinese character,so as to obtain the complete information of the learning resources.The comparative experiment proves that this method is better and can be applied in real life.