基于推荐算法的图书馆管理系统的设计与实现
摘  要
随着互联网技术的快速发展,对于图书馆管理系统的需求也在进一步提升。由于图书的种类越来越多,其相应的业务数据都不断提升,使得图书馆中的图书数据信息量已经远远超出了人工管理的水平。为了进一步给广大读者提供更为便捷的服务,可以按照读者的实际需求提供个性化定制,而当下的大多数图书馆系统中还不能满足用户的个性化定制服务。
目前大部分高校蕴藏着大量的图书借阅信息,如何利用这些信息、方便读者的借阅过程且预测读者的借阅需求,进而推荐满足读者需求的图书信息是值得研究的问题。因此,本论文的主要工作是在河北金融学院信息工程与计算机学院处设计一个图书管理与推荐系统。
本系统使用Java为开发语言,选择JSP为开发框架,SSM为系统架构、MySQL作为系统数据库,同时,为了使用户能够有更加个性化的体验,本系统采用了K-means算法将用户归类,并为用户提供了不同的图书推荐。以达到图书管系统千人千面的效果。
本课题研究的系统对目前图书馆所遇到的实际问题提出了解决方案,帮助校园更加方便地对
图书馆进行管理,其利用空间较大[5]。结合大数据技术的图书管理系统,可根据每位用户的借阅习惯,提供个性化服务,既能提高用户的阅读积极性和知识面,也能增加了用户对系统的粘度,再利用相关算法对其后台所积累的数据进行挖掘分析,提高管理者的管理效率和资源使用率。
java图书馆最新
关键词:大数据图书管理个性化推荐JavaJSPSSMMySQLK-means
ABSTRACT
With the rapid development of Internet technology, the demand for library management systems is further increasing. As there are more and more types of books, their corresponding business data are constantly improving, making the amount of book data information in the library far beyond the level of manual management. In order to further provide more convenient services to readers, personalized customization can be provided according to the actual needs of readers. However, most of the current library systems cannot meet the personalized customized services of users.
At present, most colleges and universities contain a large amount of book borrowing information. How to use this information to facilitate the borrowing process of readers and predict the borrowing needs of readers, and then recommend the book information that meets the needs of readers is a problem worthy of research. Therefore, the main work of this thesis is to design a library management and recommendation system at the School of Information Engineering and Computer, Hebei University of Finance.This system uses Java as the development language, JSP as the development framework, SSM as the system architecture, and MySQL as the system database. At the same time, in order to enable users to have a more personalized experience, the system uses the K-means algorithm to classify users. And provide users with different book recommendations. In order to achieve the effect of thousands of people in the library management system.
The system researched in this subject proposes solutions to the practical problems encountered by the library at present, and helps the campus to manage the library more conveniently, and its utilization space is larger. The book management system combined with big data technology can provide personalized services according to the borrowing ha
bits of each user, which can not only improve the user’s reading enthusiasm and knowledge, but also increase the user’s viscosity to the system, and then use related algorithms to deal with it. The data accumulated in the background is mined and analyzed to improve the management efficiency and resource utilization rate of managers.
Keywords: Big data; book management; personalized recommendation; Java; JSP; SSM; MySQL; K-means
1章 绪论    6

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