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Distributed Linear Programming for Weblog Data using Mining Techniques in Distributed Environment

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 7 - Article 3
Year of Publication: 2010
K. Suresh
Dr Sujni Paul

K Suresh and Dr Sujni Paul. Article:Distributed Linear Programming for Weblog Data using Mining Techniques in Distributed Environment. International Journal of Computer Applications 11(7):13–18, December 2010. Published By Foundation of Computer Science. BibTeX

	author = {K. Suresh and Dr Sujni Paul},
	title = {Article:Distributed Linear Programming for Weblog Data using Mining Techniques in Distributed Environment},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {11},
	number = {7},
	pages = {13--18},
	month = {December},
	note = {Published By Foundation of Computer Science}


Distributed learning discusses different strategies in which learners can communicate with each other. The different strategies are data analysis, predicting future learner in an efficient way to access the learning methods. In this paper the distributed learning has proposed an optimized solution for the fore coming learners. The idea of distributed learning is to analyse the weblog data traversed by the previous learners. Data mining is a process of mining the previously unknown data to make shape up useful knowledge or patterns from large databases. The distributed linear programming is the mathematical approach used in this paper to classify web sites from the weblog data for a specific purpose. Distributed learning approach is used in support vector machine and linear regression method. This paper recommends the fore coming learners to go through the identified web links in order to get high score.


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