高校数字图书馆嵌入式移动学习模型构建

Construction of Embedded Mobile Learning Model in University Digital Library

移动学习作为一种新型学习方式,与高校数字图书馆相结合,可为学生带来更为高效、智能的学习,也是智能学习领域重点研究内容。现阶段的高校数字图书馆嵌入式移动学习存在智能化不足、信息获取速度慢等问题,为了解决移动学习中存在的问题,构建了高校数字图书馆嵌入式移动学习模型。首先,构建基于文本概念的文本表示模型,解决向量空间模型的同义词的识别问题,并结合Jaro-Winkler算法,计算标签之间的相似性,降低文本的相似程度,提高学生的学习效率。其次,利用LLE算法降维获取的高校用户数据;通过改正正则化估计方法提取高校用户数据特征,完成用户相似度的计算,最后,基于协同过滤技术完成嵌入式移动学习模型的构建。实验结果表明,高校数字图书馆嵌入式移动学习模型推送效果与学生需求更匹配、性能更好,具有较高的实际应用价值。

As a new learning method,mobile learning combined with university digital library can bring more efficient and intelligent learning methods to students.It is also a key research content in the field of intelligent learning.In order to solve the problems in mobile learning methods,this paper constructs an embedded mobile learning model of university digital library.Firstly,a text representation model based on text concept is constructed,which solves the problem of recognition of synonyms of vector space model,and combines the Jaro-Winkler algorithm to calculate the similarity between labels,reduce the similarity of text,and improve students' learning efficiency.Then,the LLE algorithm is used to reduce the dimensionality of the obtained university user data.The characteristics of university user data are extracted by correcting the regularization estimation method,the calculation of user similarity is completed,and finally,the construction of embedded mobile learning model is completed based on collaborative filtering technology.The experimental results show that the push effect of the embedded mobile learning model of the university digital library is more compatible with the needs of students,has better performance and high practical application value.