By Topic

Combination Tree for Mining Frequent Patterns Based on Inverted List

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Liu Yong ; Dept. of Comput. & Inf. Technol., Fudan Univ., Shanghai ; Hu Yun-Fa

In this paper, a combination-tree algorithm is presented for mining frequent patterns based on inverted list. Compared with Apriori algorithm and FP-growth algorithm, our algorithm has better efficiency. Our algorithm insert items one by one with inverted list to build frequent tree, then transfer count between branches in order to make branches independent, our algorithm need only scan data set twice, can share more common items of transactions, can omit the local infrequent items, at the same time, avoid lots of recursive operations. Our performance study and theory analysis show that it is efficient in both dense datasets and sparse datasets

Published in:

Computational Intelligence and Security, 2006 International Conference on  (Volume:1 )

Date of Conference:

Nov. 2006