09 February 2010
  Welcome Guest
  Login | Help
Home
 
General Information
Transaction Series

Related Information

Login
Login ID:
Password:
 
Your Cart
There are 0 items in your cart. [View]

Adobe PDF Reader is required to view our papers:
Get Acrobat Reader




  Welcome to the WIT eLibrary

The home of the Transactions of the Wessex Institute collection, providing on-line access to papers presented at the Institute's prestigious international conferences and from its State-of-the-Art in Science & Engineering publications.

Paper Information

Finding the N Largest Itemsets

Author(s): Li Shen, Hong Shen, Paul Pritchard & Rodney Topor

Abstract:
The largest itemset in a given collection of transactions £> is the itemset that occurs most frequently in T>.

This paper studies the problem of finding the A/" largest itemsets, whose solution can be used to generate an appropri- ate number of interesting itemsets for mining association rules.

We present an efficient algorithm for finding the jV largest itemsets.

The algorithm is implemented and compared with the naive solution using the Apriori approach.

We present experimental results as well as theoretical analysis showing that our algorithm has a much better performance than the naive solution.

We also analyze the cost of our algorithm and observe that it has a polynomial time complexity in most cases of practical applications.

1 ...

Pages: 12
Size: 1,200 kb
Paper DOI: 10.2495/DATA980151

 

 

Download the Full Article

Price: US$ 30.00

You can purchase the full text version of this article in Adobe PDF format for the above price. Please click the 'Buy Paper' icon below to purchase this paper.

Send this page to a friend. Send this page to a colleague.



This paper can be found in the following book

Data Mining

Data Mining

Buy Book from
Witpress.com



Download the Full Article

You can purchase the full text version of this article in Adobe PDF format for the price listed above. Please click the 'Buy Paper' icon to the right to purchase this paper.


Copyright© 2006 by WIT Press | About Prof Carlos Brebbia
Optimised for Microsoft Internet Explorer