### 图书推荐系统
1. 概述
* apriori文件夹为数据操作。hadoop进行数据处理，apriori算法获得频繁项集。
* 数据集 [download](http://www2.informatik.uni-freiburg.de/~cziegler/BX/)
* test文件夹为java web项目。maven管理
2. 安装
* 安装maven
* 可直接使用处理完成的数据，导入freq_item.sql数据库文件
* freq_item数据库中多个表为不同置信度、支持度阈值时的数据结果，任选其一即可
* 注意更改java web项目中数据库用户名等，本项目连接username:user1,password:1
* 进入test目录，启动java web项目
```shell
mvn tomcat:7 run
```
3. 自行处理数据
* 如想自己处理数据，需要自行配置hadoop环境需重更改apriori文件夹中FreqItemSetMain类中数据地址字符串等
* 可根据需要更改置信度、支持度阈值
***
### Book recommendation system
1. Overview
* The apriori folder is a data operation. Hadoop is used for data processing, and Apriori algorithm is used to obtain frequent itemsets.
* Data set [download](http://www2.informatik.uni-freiburg.de/~cziegler/BX/)
* The test folder is a Java Web project. Maven management
2. Installation
* Installation maven
* The processed data can be directly used to import freq_ item.sql Database file
* freq_ If there are multiple tables in the item database with different confidence levels and support thresholds, you can choose one of them
* Pay attention to change the database user name in the Java Web project, and connect the project username:user1 , password:1
* Enter the test directory and start the Java Web project
```shell
mvn tomcat:7 run
```
3. Self processing data
* If you want to process data by yourself, you need to configure Hadoop environment by yourself, and you need to change the data address string in the freqitemsetmain class in the apriori folder
* The confidence and support thresholds can be changed as needed
基于springboot + hadoop的图书推荐系统源码+文档说明（高分项目）.zip （78个子文件） 
book-recommendsystem-master 
presentation.doc 7.17MB test 
README.md 2KB freq_item.sql 82.81MB apriori .classpath 24KB src core-site.xml 1KB two CountCL.java 3KB FreqItemSet.java 2KB FreqItemSetMain.java 2KB PreJob.java 3KB FreqItemSet2.java 3KB hdfs-site.xml 1KB log4j.properties 13KB three CountCL.java 3KB CountRate.java 4KB FreqItemSet.java 3KB FreqItemSetMain.java 2KB PreJob.java 3KB Insert.java 2KB FreqItemSet2.java 4KB apriori CountCL.java 3KB FreqItemSet.java 2KB FreqItemSetMain.java 984B PreJob.java 3KB FreqItemSet2.java 3KB bin core-site.xml 1KB two PreJob$PreJobReducer.class 3KB CountCL$CountCLMapper.class 2KB FreqItemSetMain.class 1KB FreqItemSet2$FreqItemSet2Combiner.class 2KB PreJob.class 2KB FreqItemSet$FreqItemSetCombiner.class 2KB CountCL.class 2KB FreqItemSet$FreqItemSetMapper.class 2KB FreqItemSet2$FreqItemSet2Mapper.class 4KB FreqItemSet.class 2KB PreJob$PreJobMapper.class 3KB FreqItemSet2.class 2KB FreqItemSet$FreqItemSetReducer.class 2KB FreqItemSet2$FreqItemSet2Reducer.class 2KB CountCL$CountCLReducer.class 3KB hdfs-site.xml 1KB log4j.properties 13KB three PreJob$PreJobReducer.class 3KB CountCL$CountCLMapper.class 2KB FreqItemSetMain.class 1KB FreqItemSet2$FreqItemSet2Combiner.class 2KB PreJob.class 2KB CountRate$CountRateMapper.class 3KB FreqItemSet$FreqItemSetCombiner.class 2KB CountCL.class 2KB FreqItemSet$FreqItemSetMapper.class 2KB FreqItemSet2$FreqItemSet2Mapper.class 4KB FreqItemSet.class 2KB PreJob$PreJobMapper.class 3KB FreqItemSet2.class 2KB FreqItemSet$FreqItemSetReducer.class 2KB CountRate$CountRateCombiner.class 2KB CountRate.class 2KB Insert.class 3KB CountRate$CountRateReducer.class 4KB FreqItemSet2$FreqItemSet2Reducer.class 2KB CountCL$CountCLReducer.class 3KB apriori PreJob$PreJobReducer.class 3KB CountCL$CountCLMapper.class 2KB FreqItemSetMain.class 770B FreqItemSet2$FreqItemSet2Combiner.class 2KB PreJob.class 2KB FreqItemSet$FreqItemSetCombiner.class 2KB CountCL.class 2KB FreqItemSet$FreqItemSetMapper.class 2KB FreqItemSet2$FreqItemSet2Mapper.class 3KB FreqItemSet.class 2KB PreJob$PreJobMapper.class 3KB FreqItemSet2.class 2KB FreqItemSet$FreqItemSetReducer.class 2KB FreqItemSet2$FreqItemSet2Reducer.class 2KB CountCL$CountCLReducer.class 3KB .project 418B资源评论
