稀疏矩阵的概念与应用  

The Concept and Application of Sparse Matrices

作　　者：许春荣 买买提依明·哈斯木 XU Chunrong;MAMTIMIN Kasim(Guangzhou College of Commerce,Guangzhou Guangdong 511363,China)

机构地区：[1]广州商学院,广东广州511363

出　　处：《信息与电脑》2023年第21期254-256,共3页Information & Computer

摘　　要：稀疏矩阵在数据存储、机器学习、图像处理及文本处理方面有广泛的应用。在数据结构等一些课程中,教材会介绍稀疏矩阵,包括压缩存储方法等内容。由于稀疏矩阵的讲解比较少,理论的内容比较多,案例讲解较少,学生不易理解。为了让学生更好地理解稀疏矩阵及其应用,通过垃圾邮件过滤分类的案例,对比采用稠密型矩阵和稀疏矩阵两种形式,验证稀疏矩阵在存储和训练运算方面的优越性。Sparse matrix is widely used in data storage,machine learning,image processing and text processing.In some courses,such as data structures,sparse matrices are introduced,including compressed storage methods.Due to less explanation of sparse matrix,more theoretical content,less case explanation,it is difficult for students to understand.In order to give students a better understanding of sparse matrix and its application,this paper compares two forms of dense matrix and sparse matrix through spam filtering classification cases,and verifies the superiority of sparse matrix in storage and training operations.

关 键 词：稀疏矩阵 数据结构 垃圾邮件过滤 案例理解 

分 类 号：G612[文化科学—学前教育学]