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Use of Data Mining Tools in the Fields of Tea Cultivation and Tea Industry of Assam

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International Journal of Computer Applications
© 2011 by IJCA Journal
Number 1 - Article 1
Year of Publication: 2011
Authors:
Sadiq Hussain
Nayeemuddin Ahmed
10.5120/3813-5266

Sadiq Hussain and Nayeemuddin Ahmed. Article:Use of Data Mining Tools in the Fields of Tea Cultivation and Tea Industry of Assam. International Journal of Computer Applications 31(4):27-41, October 2011. Full text available. BibTeX

@article{key:article,
	author = {Sadiq Hussain and Nayeemuddin Ahmed},
	title = {Article:Use of Data Mining Tools in the Fields of Tea Cultivation and Tea Industry of Assam},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {31},
	number = {4},
	pages = {27-41},
	month = {October},
	note = {Full text available}
}

Abstract

Data mining has great potential in the fields of tea cultivation and tea industry of Assam for exploring the hidden patterns in the data sets of the domain. These patterns can be utilized for tea cultivation analysis. However, the available raw data are widely distributed, heterogeneous in nature, and voluminous. These data need to be collected in an organized form. This collected data can be then integrated to form an information system. Data mining technology provides a user-oriented approach to novel and hidden patterns in the data. Data mining and statistics both strive towards discovering patterns and structures in data. Statistics deals with heterogeneous numbers only,where data mining deals with heterogeneous fields.

Reference

  • J. T. Tou and R. C. Gonzalez, "Pattern recognition principles," Addison-Wesley, London, 1974.
  • K. J. Cios, W. Pedrycz, R. W. Swiniarski, and L. A. Kurgan, "Data mining: A knowledge discovery approach," Springer, New York, 2007.
  • Rakesh Agrawal and Ramakrishnan Srikant. Fast algorithms for mining association rules in large databases. Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, pages 487-499, Santiago, Chile, September 1994
  • R. O. Duda, P. E. Hart, and D. G. Stork, "Pattern classification,"Wiley,2001.
  • T. Hastie, R. Tibshirani, and J. Friedman, "The elements of statistical learning: Data mining, inference, and prediction," Springer, New York, 2001.
  • Aggarwal Charu and Yu Philip.Mining large itemsets for association rules.Bulletin Of the IEEE Computer Society Technical Committee on Data Engineering,21,no.1,March 1998
  • Toivonen H.,Klemettinen M.,Ronkainen P.,Hatonen K and Mannila H.”Pruning and grouping discovered association rules”.Workshop on Statistical Machine Learning and Knowlege Discovery in Databases.1995
  • Arun K Pujari ”Data Mining Techniques”Universities Press,Pages 69-109,February 2001
  • Alex Beyson and Steve Smith , ”Data Warehousing,Data Mining and OLAP” 2004.