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Iterative Approach for Frequent Set Mining Using Hadoop Over Cloud Environment
, Narayan S, , , Ramasubbareddy S.
Published in Springer Singapore
Volume: 105
Pages: 399 - 405
Cloud computing initially gained popularity as it offered an alternative for handling the ever-growing size of data. One of the main advantages of Cloud computing is parallel processing of data, which causes the effect of pooling the resources of various systems. The proposed project aims to implement the feature for the purpose of data mining and will use the Apriori Algorithm to demonstrate the results. Hadoop platform will be utilized for this project. The system will receive a dataset and redistribute it to the nodes of the cloud. Here, Apriori algorithm will be applied upon the sections of the dataset and the results will then be combined to obtain the frequent itemsets in the global data. Using the frequent item sets, rule mining will be achieved. © Springer Nature Singapore Pte Ltd. 2019.
About the journal
JournalData powered by TypesetSmart Intelligent Computing and Applications Smart Innovation, Systems and Technologies
PublisherData powered by TypesetSpringer Singapore
Open AccessNo