CFP last date
20 March 2024
Reseach Article

Mining Medicinal Information using Flowers

by S. Vigneswari, S. S. Dhenakaran
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 22
Year of Publication: 2014
Authors: S. Vigneswari, S. S. Dhenakaran

S. Vigneswari, S. S. Dhenakaran . Mining Medicinal Information using Flowers. International Journal of Computer Applications. 95, 22 ( June 2014), 15-20. DOI=10.5120/16726-6915

@article{ 10.5120/16726-6915,
author = { S. Vigneswari, S. S. Dhenakaran },
title = { Mining Medicinal Information using Flowers },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 22 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 15-20 },
numpages = {9},
url = { },
doi = { 10.5120/16726-6915 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:20:07.320960+05:30
%A S. Vigneswari
%A S. S. Dhenakaran
%T Mining Medicinal Information using Flowers
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 22
%P 15-20
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

Mining is the art of finding unknown patterns from voluminous data. Medical data mining becomes major concern now a day. The objective of the proposed work is the association of data and prediction of treatment to cure diseases using flowers. The data source used here is the collection of flowers, which have separate medicinal values. Based upon the medicinal worthiness, the vitamin contents, in the flowers, prediction is made for the treatment of diseases. For this purpose, the association rule mining technique is taken into account. Association rules represent knowledge embedded in data sets as probabilistic insinuation and are closely related to computation of frequent item sets that occurs on the given data set.

  1. Abdullah Saad Almalaise Alghamdi, "Efficient Implementation of FP Growth Algorithm-Data Mining on Medical Data", in International Journal of Computer Science and Network Security, VOL. 11 No. 12, December 2011, pp: 7 – 16.
  2. Agrawal, R. , Imielinski, T. & Swami, A. (1993). "Database Mining: A Performance Perspective". IEEE Transactions on Knowledge and Data Engineering5 (6): 914–925.
  3. Dan A. Simovici, "Data Mining of Medical Data: Opportunities and Challenges in Mining Association Rules ", pp: 1-25.
  4. N. Deepika, K. Chandra Shekar, D. Sujatha, "Association Rules for classification of Heart–AttackPatients", in International Journal of Advanced engineering Sciences and Technologies, Vol 11, issue 2, pp:253 – 257.
  5. Fayyad, U. M. , Piatetsky-Shapiro, G. & Smyth, P. (1996a). "From Data Mining to Knowledge Discovery: An Overview". In Fayyad, U. M. , Piatetsky-Shapiro, G. , Smyth, P. & Uthurusamy, R. (eds. )Advances in Knowledge Discovery and Data Mining, 1–36. AAAI Press/MIT Press.
  6. Feelders, A. , Daniels, H. and Holsheimer,M. (2000) 'Methodological and Practical Aspects of Data Mining', Information and Management, pp. 271-281.
  7. Gang Fang, Zu-Kuan Wei, Yu-Lu Liu," "An algorithm of improved association rules mining", Proceedings of the Eighth International Conference on Machine Learning and Cybernetics, Baoding, 12-15 July 2009.
  8. Hai Wang, Shouhong Wang, "Medical Knowledge Acquisition through Data Mining", Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education.
  9. Hian Chye Koh and Gerald Tan, "The data mining applications in healthcare management", in Journal of Healthcare information Management — Vol. 19, No. 2, pp: 64 – 72.
  10. MA. Jabbar,Dr. pritichandra, L. Deekshatulu,, "Cluster based association rule mining for heart attack prediction", in Journal of Theoretical and Applied Information Technology", vol 32, no 2, pp: 196 – 201.
  11. Krzysztof J. Cios and G. William Moore, "Uniqueness of Medical Data Mining", Artificial Intelligence in Medicine Journal, 2002.
  12. Larose T. Daniel (2005). "Discovering Knowledge in Data: An Introduction to Data Mining", John Wiley & Sons, Inc. , Hoboken, New Jersey
  13. Tipawan Silwattananusarn, KulthidaTuamsuk," Data Mining and Its Applications for Knowledge Management .
  14. Mrs S. M Uma and Dr. E. Kirubakaran,"Intelligent Heart Diseases Prediction System Using A New Hybrid Metaheuristic Algorithm",International Journal of Engineering Research & Technology (IJERT)Vol. 1 Issue 8, October – 2012. .
  15. M. ANBARASI,E. ANUPRIYA and N. CH. S. N. IYENGAR, "Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic", International Journal of Engineering Science and Technology Vol. 2(10), 2010, 5370-5376 .
  16. Ramya Rathan,Shridhar and R Balasubramanian S ,"Association Rule- Spatial Data Mining Approach for Exploration of Endometrial Cancer Data", International Journal of Advanced Research in Computer Science and Software Engineering,Volume 3, Issue 10, October 2013 ISSN: 2277 128X.
  17. P. Sunil Kumar and Ashok Kumar Panda," USE OF ASSOCIATION RULE MINING IN HIGHER SECONDARY EDUCATION IN ODISHA ",International Journal on Advanced Computer Theory and Engineering (IJACTE),ISSN (Print) : 2319 – 2526, Volume-2, Issue-6, 2013
Index Terms

Computer Science
Information Sciences


Data Mining Association Rule Mining Medicinal flowers prediction.