Research Article
Article:Mining Maximal Frequent Item Sets
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 10 - Issue 3 |
| Published: November 2010 |
| Authors: Dr. S.S. Mantha, Madhuri Rao, Ashwini Anil Mane, Anil S. Mane |
10.5120/1463-1978
|
Dr. S.S. Mantha, Madhuri Rao, Ashwini Anil Mane, Anil S. Mane . Article:Mining Maximal Frequent Item Sets. International Journal of Computer Applications. 10, 3 (November 2010), 12-15. DOI=10.5120/1463-1978
@article{ 10.5120/1463-1978,
author = { Dr. S.S. Mantha,Madhuri Rao,Ashwini Anil Mane,Anil S. Mane },
title = { Article:Mining Maximal Frequent Item Sets },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 10 },
number = { 3 },
pages = { 12-15 },
doi = { 10.5120/1463-1978 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A Dr. S.S. Mantha
%A Madhuri Rao
%A Ashwini Anil Mane
%A Anil S. Mane
%T Article:Mining Maximal Frequent Item Sets%T
%J International Journal of Computer Applications
%V 10
%N 3
%P 12-15
%R 10.5120/1463-1978
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Data mining or knowledge discovery in databases (KDD) is a collection of exploration techniques based on advanced analytical methods and tools for handling a large amount of information. Mining association rule is a main content of data mining research at present, and emphasizes particularly is finding the relation of different items in the database. How to generate frequent item sets is the key and core. It is an important aspect in improving mining algorithm that how to decrease item set candidates in order to generate frequent item set effectively.
References
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- http://en.wikipedia.org/wiki/Apriori_algorithm.
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- http://fimi.cs.helsinki.fi/
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