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  Published Paper Details:

  Paper Title

A SURVEY ON ANALYSIS, EVALUATION AND IMPROVEMENT OF GRAPH MINING ALGORITHMS USING DUPLICATE REDUCTION TECHNIQUE

  Authors

  Shreya Appa Langote,  V.V. Pottigar

  Keywords

Graph mining, substructure discovery, constraint-based heuristics, duplicates reduction, partitioning of graphs

  Abstract


At the center of graph mining lies free extension of bases where a base or subgraph autonomously develops into various bigger bases in every cycle. Such a free development, perpetually, prompts the age of copies. Within the sight of chart segments, copies are created both inside and across allotments. Wiping out these copies brings about age and capacity cost as well as extra calculation for its end. Essential point is to plan methods to decrease creating copy foundations as we show that they can't be dispensed with. Proposed philosophy presents three requirement based enhancement strategies, each essentially improving the general mining cost by diminishing the quantity of copies produced. These options give adaptability to pick the correct procedure dependent on chart properties. Proposed philosophy tests show noteworthy advantages of these imperatives regarding capacity, calculation, and correspondence cost (explicit to divided methodologies) across graphs with differed qualities.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2007002

  Paper ID - 196437

  Page Number(s) - 7-11

  Pubished in - Volume 8 | Issue 7 | July 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Shreya Appa Langote,  V.V. Pottigar,   "A SURVEY ON ANALYSIS, EVALUATION AND IMPROVEMENT OF GRAPH MINING ALGORITHMS USING DUPLICATE REDUCTION TECHNIQUE", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 7, pp.7-11, July 2020, Available at :http://www.ijcrt.org/papers/IJCRT2007002.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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