Mining Association Rules in Cloud

dc.contributor.authorRoy, Pallavi
dc.date.accessioned2012-08-01T14:11:57Z
dc.date.available2012-08-01T14:11:57Z
dc.date.issued2012
dc.description.abstractThe association rule mining was implemented in Hadoop. An association rule mining helps in finding relation between the items or item sets in the given data. The performance of the algorithm was evaluated by testing it in the cloud (EC2) by increasing the number of nodes in the testing set up. The association rules are developed on the basis of the frequent item set generated from the data. The frequent item set were generated following the Apriori algorithm. As the input data and number of distinct items in the data set is large, lots of space and memory is required, so Hadoop was used, as Hadoop provide parallel, scalable, robust framework in the distributed environment.en_US
dc.identifier.urihttps://hdl.handle.net/10365/21748
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU Policy 190.6.2
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
dc.subject.lcshApache Hadoop.en_US
dc.subject.lcshAssociation rule mining.en_US
dc.subject.lcshComputer algorithms.en_US
dc.subject.lcshCloud computing.en_US
dc.titleMining Association Rules in Clouden_US
dc.typeMaster's paperen_US
ndsu.advisorLi, Juan
ndsu.collegeEngineeringen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.departmentComputer Scienceen_US
ndsu.programSoftware Engineeringen_US

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Pallavi_Report.pdf
Size:
528.78 KB
Format:
Adobe Portable Document Format
Description:
Pallavi Roy

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description: