发布时间 : 星期四 文章基于Knn算法的图书推荐系统(毕业设计)更新完毕开始阅读b5dabdc390c69ec3d4bb7528
华北科技学院毕业设计
目录
基于Knn算法的图书推荐系统 ...................................................................................................................... I Book recommendation system based on Knn algorithm ................................................................................. II 第1章 绪论 ............................................................................................................................................ 1
1.1 1.2 1.3 1.4 第2章
应用背景 .................................................................................................................................... 1 系统功能 .................................................................................................................................... 2 系统预览 .................................................................................................................................... 2 系统特点 .................................................................................................................................... 1 开发环境及工具......................................................................................................................... 2
2.1系统开发环境................................................................................................................................... 2 2.2系统架构模型................................................................................................................................... 2 2.3系统开发技术................................................................................................................................... 3 2.3.1 R语言简介 ............................................................................................................................ 3
2.3.2数据库技术简介 .................................................................................................................... 3 2.3.3 Java简介 ............................................................................................................................... 4
第3章 系统设计与数据库 ..................................................................................................................... 5
3.1系统设计 .......................................................................................................................................... 5
3.1.1 系统功能模块划分 ............................................................................................................... 5 3.2数据库结构 ...................................................................................................................................... 5 第4章 K最近邻分类（Knn）算法介绍 .................................................................................................. 6
4.1 Knn算法简介 ................................................................................................................................... 6 4.2 算法流程 ......................................................................................................................................... 6 4.3 算法优缺点 ..................................................................................................................................... 7 4.3.1 优点 ...................................................................................................................................... 7
4.3.2 缺点 ...................................................................................................................................... 7
第5章 Knn算法在图书推荐系统的实现 ................................................................................................... 8
5.1 训练集数据train.data ...................................................................................................................... 8 5.2建立读者-书目矩阵 ......................................................................................................................... 9 5.3计算书目距离矩阵distance ........................................................................................................... 10 5.4计算读者和书目的关系程度 ......................................................................................................... 10 5.5计算用户的推荐书目id .................................................................................................................11 5.6 查询推荐书目的具体信息 ............................................................................................................ 13 第6章 SQL Server数据库、Java语言与R的组合 ................................................................................ 14
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图书推荐系统
6.1 简述 ............................................................................................................................................... 14 6.2 SQL Server数据库与R语言 ........................................................................................................ 14 6.3 R语言与Java语言 ........................................................................................................................ 15 参考文献 ...................................................................................................................................................... 16 致谢 .............................................................................................................................................................. 17 附录 .............................................................................................................................................................. 18
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华北科技学院毕业设计
基于Knn算法的图书推荐系统
摘要：互联网的出现和普及给用户带来了大量的信息，满足了用户在信息时代对信息的需求的同时，也使得用户在面对大量信息时无法从中获得对自己真正有用的那部分信息，而产生所谓的信息超载问题，推荐系统就这样应运而生。推荐系统现已广泛应用于很多领域，其中最典型并具有良好的发展和应用前景的领域就是电子商务领域。个性化推荐系统是建立在海量数据挖掘基础上的一种高级商务智能平台，以帮助电子商务网站为其顾客购物提供完全个性化的决策支持和信息服务。同时学术界对推荐系统的研究热度一直很高，逐步形成了一门独立的学科。
本文介绍的推荐系统，一方面根据学校的图书借阅情况，构建出基于Knn算法的图书推荐系统，可以解决同学们借书没有头绪，借不到适合自己的书等等问题，另一方面实现了数据、算法、成果展示的分离，使得程序设计、大数据处理、前端展示的分工更加明确简洁。
本系统采用了统计领域广泛使用的R软件，适于数据存储与挖掘的SQL Server 2008，以及适用于前端展示的Java语言，通过三者的协调互助，共同完成推荐系统的数据存储、挖掘以及展示工作。
关键词：推荐系统 Knn算法 专属推荐 大数据挖掘 R软件
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图书推荐系统
Book recommendation system based on Knn algorithm
Abstract: The emergence and popularization of the Internet users to bring a great deal of information, meet the users at the same time the need for information in the information age, but also makes the user in the face of a large amount of information cannot be obtained from that part of the information they really useful, and produce the information overload the so-called problems, recommendation system comes. Recommendation system has been widely used in many fields, among which the most typical and has good prospects for the development and application of the field is the field of electronic commerce. Personalized recommender system is established on the basis of a senior mining business intelligence platform in the massive data, in order to help e-commerce sites provide complete personalized decision support and information service for the customer shopping. At the same time, the research heat system to recommend the academic community has been very high, and gradually formed an independent discipline.
Recommendation system is introduced in this paper, hand according to books borrowing situation of the school, build a recommendation system based on Knn algorithm library, can solve the students borrow books have no clue, borrow not suitable for their own books and so on, on the other hand to achieve the separation of data, algorithms, the results show that the program design, large data, processing, front-end display division more clear and concise.
This system adopts the widely used R software for statistical field, data storage and data mining in SQL Server 2008, and the application of Java language in the front display, through the coordination of the three cooperation, jointly completed recommendation system for data storage, and display the work of mining.
Key words：Recommendation system; Knn algorithm; exclusive recommendation ; large data mining ; R software
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