Elite Sequence Mining of Big Data using Hadoop Mapreduce

Authors

  • P. Amarendra Reddy

  • O Ramesh

  • . .

Received date: October 1, 2018

Accepted date: October 1, 2018

Published date: October 2, 2018

DOI:

https://doi.org/10.14419/ijet.v7i4.10.20696

Keywords:

Big data, MAPREDUCE, SVD, LSI.

Abstract

Text mining can deal with unstructured information. The proposed work extricates content from a PDF report is changed over to plain content configuration; at that point record is tokenized and serialized. Record grouping and classification is finished by discovering similarities between reports put away in cloud. Comparable archives are distinguished utilizing Singular Value Decomposition (SVD) strategy in Latent Semantic Indexing (LSI). At that point comparative records are assembled together as a group. A similar report is done between LFS (Local File System) and HDFS (HADOOP DISTRIBUTED FILE SYSTEM) as for rate and dimensionality. The System has been assessed on genuine records and the outcomes are classified.

 

 

References

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How to Cite

Amarendra Reddy, P., Ramesh, O., & ., . (2018). Elite Sequence Mining of Big Data using Hadoop Mapreduce. International Journal of Engineering and Technology, 7(4.10), 19-23. https://doi.org/10.14419/ijet.v7i4.10.20696

Received date: October 1, 2018

Accepted date: October 1, 2018

Published date: October 2, 2018