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Associated data mining algorithm under cloud computing environment

Author: ZhaoHu
Tutor: YangBo
School: University of Electronic Science and Technology
Course: Mechanical Manufacturing and Automation
Keywords: Cloud Computing MapReduce Apriori Hadoop
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 791
Quote: 0
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Abstract


With the progress of manufacturing technology , hardware manufacturing costs are getting lower and lower , more and more multicore cpu, massive data hard disk of the computer - based programming model makes it unable to effectively use the growing number of computing resources , so cloud calculated bred . Cloud computing will be such a huge surplus computing storage resource integration for a pool of resources to publish the computing power to every corner of the way through the network , to make people like hydropower , using the calculated storage resources . Data mining need computing storage volume is huge , so the combination of cloud computing and data mining can effectively control the computational cost , enhance the efficiency of data mining , break through the bottleneck of traditional data mining restrictions . Hadoop framework as the industry 's most famous open source distributed computing framework by using MapReduce parallel model , the effective integration of existing computing storage capacity , providing a powerful distributed computing power . On the basis of the mining algorithms Apriori and Hadoop framework associated data in the study classic , complete the following tasks: 1. Apriori algorithm into the MapReduce model to achieve the Apriori parallel transformation , and then compress the original transaction set to improve the Apriori algorithm in Hadoop under the framework of the performance, and ultimately to achieve high scalability for MapReduce-Apriori algorithm in cloud computing environments . Call record data set as an example , based on the overall call record data and personal call data associated data mining , MapReduce-Apriori algorithm used in the mining , mining meaningful association rules from the data . Washing stage 3 in the call data , Hive Hadoop for cleaning , to achieve a data cleaning tool having a high expansion capacity . The design and testing of distributed computing services private cloud .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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