|Review Paper on Graph Based Approach for Mining Health Examination Records Using Views|
|Reshma Ravi1 , emya R2|
1 College Of Engineering Perumon, APJ Abdul Kalam Technological University,kerala ,India.
2 College Of Engineering Perumon, APJ Abdul Kalam Technological University,kerala ,India.
|Correspondence should be addressed to: firstname.lastname@example.org.|
Section:Review Paper, Product Type: Journal Paper
Volume-5 , Issue-11 , Page no. 64-67, Nov-2017
Online published on Nov 30, 2017
Copyright © Reshma Ravi, Remya R . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Reshma Ravi, Remya R, “Review Paper on Graph Based Approach for Mining Health Examination Records Using Views”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.11, pp.64-67, 2017.
MLA Style Citation: Reshma Ravi, Remya R "Review Paper on Graph Based Approach for Mining Health Examination Records Using Views." International Journal of Computer Sciences and Engineering 5.11 (2017): 64-67.
APA Style Citation: Reshma Ravi, Remya R, (2017). Review Paper on Graph Based Approach for Mining Health Examination Records Using Views. International Journal of Computer Sciences and Engineering, 5(11), 64-67.
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|Answering Queries using Views is proven as an effective technology for querying real life graphs. Real life graphs are really large, so if a query arises from such graph it’s a troublesome process. Answering using views is an easy method. When SHG health algorithm is combined with answering queries using views, we can analyze the medical data and based on that data we can predict whether a health examination participant is at risk, if yes what the key associated disease category is. This helps to predict the risks at an early stage. Medical data are usually large and distributed. So we use efficient algorithms like maximally contained rewriting, Minimal containment along with the SHG algorithm to analyze medical data. Semi supervised Heterogeneous algorithm is an efficient algorithm. Maximally contained rewriting algorithm helps to find an approximate answer to the query even if it is not contained in the views.|
|Key-Words / Index Term :|
|Pattern containment,SHG,Minimal Containment|
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