Mining of Frequent Itemset in Hadoop
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
Information are produced from different sources, the quick move from computerized advances has prompted development of huge information. Terabytes of information is produced every day by modern information systems and digital technologies like Internet of Things and distributed computing. In Data Mining, it takes out information from large sets of data or it is the procedure of knowledge mining from large collection of data. The large amount of data is available in the Information Industry. FIM is the most important concept in mining. Association Rule mining and Frequent item set mining are well known techniques for data mining which needs whole dataset into fundamental memory (main memory) for processing, however extensive datasets do not fit into fundamental memory. To defeat this limitation MapReduce is utilized for parallel processing of Big Data having elements such as high scalability and robustness which helps to handle problem of large datasets. The Big Data mining is essential in order to take out value from massive amount of data which give better insights using proficient techniques. This paper investigates the potential effect of FIM in big data and data mining.
Authors and Affiliations
Kavitha Mohan, Talit Sara George
Keywords
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