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DOI: 10.14569/IJACSA.2016.071206
PDF

RSECM: Robust Search Engine using Context-based Mining for Educational Big Data

Author 1: D. Pratiba
Author 2: G. Shobha

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 12, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: With an accelerating growth in the educational sector along with the aid of ICT and cloud-based services, there is a consistent rise of educational big data, where storage and processing become the prime matter of challenge. Although many recent attempts have used open source framework e.g. Hadoop for storage, still there are reported issues in sufficient security management and data analyzing problems. Hence, there is less applicability of mining techniques for upcoming search engine due to unstructured educational data. The proposed system introduces a technique called as RSECM i.e. Robust Search Engine using Context-based Modeling that presents a novel archival and search engine. RSECM generates its own massive stream of educational big data and performs the efficient search of data. Outcome exhibits RSECM outperforms SQL based approaches concerning faster retrieval of the dynamic user-defined query.

Keywords: Big Data; Context; Cloud; Educational Data; Hadoop; Search Engine

D. Pratiba and G. Shobha, “RSECM: Robust Search Engine using Context-based Mining for Educational Big Data” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071206

@article{Pratiba2016,
title = {RSECM: Robust Search Engine using Context-based Mining for Educational Big Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071206},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071206},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {D. Pratiba and G. Shobha}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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