Open AccessElite Sequence Mining of Big Data using Hadoop Mapreduce
Author(s) -
P. Amarendra Reddy,
O Ramesh
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.10.20696
Subject(s) - computer science , search engine indexing , information retrieval , data mining , sequence (biology) , big data , curse of dimensionality , point (geometry) , cloud computing , singular value decomposition , database , artificial intelligence , operating system , mathematics , geometry , biology , genetics
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.