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Education cloud application statistics method based on parallelized association rule algorithm

A statistical method, technology of cloud application, applied in the field of computer statistics

Active Publication Date: 2015-04-29
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In the prior art, there is no method for mining association rules of data through data preprocessing and data modeling based on the MapReduce framework

Method used

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  • Education cloud application statistics method based on parallelized association rule algorithm
  • Education cloud application statistics method based on parallelized association rule algorithm
  • Education cloud application statistics method based on parallelized association rule algorithm

Examples

Experimental program
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Embodiment Construction

[0011] A statistical method for educational cloud applications based on a parallelized association rule algorithm, the specific steps are as follows:

[0012] Step 1. Obtain log information data from the education cloud server and regularly upload it to the distributed file system HDFS of the cluster nodes;

[0013] Step 2, using the log information data stored in HDFS as source data to perform database data modeling;

[0014] Step 3: After the source data is modeled, it is stored in HDFS in the form of a data item set file, and each line represents a visitor's click stream sequence; before frequent item set and association rule mining, the binary representation is used, and the The data item set is converted into a Boolean matrix, and the Boolean matrix is ​​stored in the distributed file system HDFS;

[0015] Step 4. Mining association rules: Parallelize and optimize traditional mining methods based on MapReduce. The specific steps are:

[0016] 10) Scan the Boolean matrix...

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Abstract

The invention relates to an education cloud application statistics method based on a parallelized association rule algorithm. The method comprises the following steps of firstly performing data modeling to education cloud application access conditions and storing source data in an HDFS (Hadoop Distributed File System) in the form of Boolean matrix; secondly performing parallelized optimization to the association rule algorithm based on a Map Reduce framework, respectively compiling a Map function and a Reduce function, and performing mining analysis to the source data stored in the HDFS, thereby obtaining the visitor's using status of the education cloud application and recommending characteristics. According to the technical scheme of the method, the frequency of scanning data item sets is greatly reduced and the I / O (Input / Output) consumption of the system is reduced.

Description

technical field [0001] The invention relates to a statistical method for educational cloud applications based on a parallelized association rule algorithm, and belongs to the technical field of computer statistics. Background technique [0002] In recent years, with the development of the Internet and cloud computing technology, the speed and scale of data generation have greatly exceeded the past. Massive data contains a lot of value. How to use data quickly and effectively is a major challenge we face in the era of big data. The education cloud platform is the migration of cloud computing technology to the education field, including all the hardware computing resources necessary for education informatization. After these resources are virtualized, they provide users with a platform to provide education cloud services in the form of cloud applications. The education cloud platform deploys education cloud applications on the SaaS (Software as a service) layer, accesses them...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/1737G06F16/182
Inventor 袁东风王宏宾刘萍
Owner SHANDONG UNIV
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