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A Biomedical Search Support System for Improving the Data Search Accuracy

by Vikas Ransore, Jagdish Raikwal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 18
Year of Publication: 2015
Authors: Vikas Ransore, Jagdish Raikwal
10.5120/21799-5103

Vikas Ransore, Jagdish Raikwal . A Biomedical Search Support System for Improving the Data Search Accuracy. International Journal of Computer Applications. 122, 18 ( July 2015), 12-17. DOI=10.5120/21799-5103

@article{ 10.5120/21799-5103,
author = { Vikas Ransore, Jagdish Raikwal },
title = { A Biomedical Search Support System for Improving the Data Search Accuracy },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 18 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 12-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number18/21799-5103/ },
doi = { 10.5120/21799-5103 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:53.080196+05:30
%A Vikas Ransore
%A Jagdish Raikwal
%T A Biomedical Search Support System for Improving the Data Search Accuracy
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 18
%P 12-17
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Medical domain is a huge scientific domain where a large amount of data is available for analysis and discovery. In this proposed work a search improvement technique is suggested which provides guidelines for finding appropriate data during medicine search. That is because the basic search systems contains three major modules first query interface, second for search methodology and finally search ranking. User provide input to the search interface than the search system find the data from database according to the user query, finally results are ranked according to the relevancy of the user query. The proposed improvement is implemented on the query input phase for improving the user query for finding the more accurate and nearer medicines from the database.

References
  1. Radu Dragusina, Paula Petcua, Christina Lioma,Birger Larsend, Henrik L. Jørgensene, Ingemar J. Coxa, Lars Kai Hansena, PeterIngwersend, Ole Winthera, "FindZebra: A search engine for rare diseases", 23 February 2013, DOI:10. 1016/j. bbr. 2011. 03. 031
  2. Aarti Kaushik, Gurdev Singh & Anupam Bhatia, "SVM Classification in Multiclass Letter Recognition System", Global Journal of Computer Science and Technology, Software & Data Engineering, Volume 13 Issue 9 Version 1. 0 Year 2013
  3. NATHAN HALKO, PER-GUNNAR MARTINSSON, YOEL SHKOLNISKY, AND MARK TYGERT, "AN ALGORITHM FOR THE PRINCIPAL COMPONENT ANALYSIS OF LARGE DATA SETS", http://amath. colorado. edu/faculty/martinss/Pubs/2010_07_05_outofcore. pdf
  4. Gang Luo, "Design and Evaluation of the iMed Intelligent Medical Search Engine",IEEE 25th International Conference on Data Engineering, 2009. ICDE '09
  5. Ian H. Witten, "Text mining", Computer Science, University of Waikato, Hamilton, New Zealand
  6. Rasmus Bro and Age K. Smilde, "Principal component analysis", DOI: 10. 1039/C3AY41907J (Tutorial Review) Anal. Methods, 2014, 6, 2812-2831
  7. James Kwok, "Kernel Methods in Machine Learning", Department of Computer Science and Engineering Hong Kong University of Science and Technology, 2006.
  8. Asa Ben-Hur, Jason Weston, "A User's Guide to Support Vector Machines," Department of computer Science Colorado State University.
  9. Ramus Bro and Age K. Smilde, "Principal component analysis", DOI: 10. 1039/C3AY41907J (Tutorial Review Anal. Methods, 2014, 6, 2812-2831)
Index Terms

Computer Science
Information Sciences

Keywords

Text mining support vector machine (svm) principal component analysis (pca) biomedical research.