UP-Growth: An Efficient Algorithm for High Utility Itemset Mining

author: Cheng-Wei Wu, Department of Computer Science and Information Engineering, National Cheng Kung University
published: Oct. 1, 2010,   recorded: July 2010,   views: 7430
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. Although a number of relevant approaches have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets. Such a large number of candidate itemsets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility itemsets. In this paper, we propose an efficient algorithm, namely UP-Growth (Utility Pattern Growth), for mining high utility itemsets with a set of techniques for pruning candidate itemsets. The information of high utility itemsets is maintained in a special data structure named UP-Tree (Utility Pattern Tree) such that the candidate itemsets can be generated efficiently with only two scans of the database. The performance of UP-Growth was evaluated in comparison with the state-of-the-art algorithms on different types of datasets. The experimental results show that UP-Growth not only reduces the number of candidates effectively but also outperforms other algorithms substantially in terms of execution time, especially when the database contains lots of long transactions.

See Also:

Download slides icon Download slides: kdd2010_wu_uge_01.ppt (3.6┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 cmamatha, April 30, 2014 at 7:58 a.m.:

thanks for this lecture video i think this is helpful for my project


Comment2 siva, October 18, 2016 at 8:29 a.m.:

Thanks for informative video. Its really helpfull. It is good source of UP growth algorithm

Write your own review or comment:

make sure you have javascript enabled or clear this field: