Combined Inference Approach for Large Scale Ontologies based on Map Reduce Paradigm

Authors

  • K. Lakshmi Rupa  Department of Computer Science and Engineering, Annamacharya Institute of Technology and Sciences, Tirupati, Andhra Pradesh, India
  • Dr. S. S. Arumugam  Department of Computer Science and Engineering, Annamacharya Institute of Technology and Sciences, Tirupati, Andhra Pradesh, India

Keywords:

Balanced Partition, large information, four-dimensional bar chart, variety-total question

Abstract

In blessing technique, an progressive and meted out deduction procedure for Goliath scale ontology's via creating use of Map curb, that acknowledges unbalanced execution thinking and runtime searching, specifically for progressive present’s base. With the assistance of constructing up modification induction lush territory and powerful assertion triples, the potential is clearly brought down and therefore the thinking system is disentangled and quickened. At long final, a mannequin method is connected to a Hadoop constitution and therefore the trial influence approves the convenience and adequacy of the projected procedure. We tend to place in energy the FastRAQ methodology on the UNIX system stage, and appraisal it’s effectively with around 10 billion aptitudes records. take a look at results exhibit that FastRAQ presents assortment combine inquiry have an effect on at intervals an amount interim 2 requests of activity drop than that of Hive, whilst the relative mistake is prevented than third throughout the given self-belief short-time.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-12-31

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Volume 2, Issue 6, November-December-2017

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Research Articles

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How to Cite

[1]
K. Lakshmi Rupa, Dr. S. S. Arumugam, " Combined Inference Approach for Large Scale Ontologies based on Map Reduce Paradigm, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.703-708 , November-December-2017.