2010 UPGrowthAnEfficientAlgorithmfor

• (Tseng et al., 2010) ⇒ Vincent S. Tseng, Cheng-Wei Wu, Bai-En Shie, and Philip S. Yu. (2010). “UP-Growth: An Efficient Algorithm for High Utility Itemset Mining.” In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2010). doi:10.1145/1835804.1835839

Subject Headings:

Notes

• slides http://making.csie.ndhu.edu.tw/seminar/making/papers/PPT/UP-Growth%20An%20Efficient%20Algorithm%20for%20High%20Utility%20Itemset%20Mining(SIGKDD2010).pptx

Cited By

• ~1 http://scholar.google.com/scholar?q=%22UP-Growth%3A+an+efficient+algorithm+for+high+utility+itemset+mining%22+2010
• http://portal.acm.org/citation.cfm?id=1835839&preflayout=flat#citedby

Quotes

Abstract

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. 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.

References

,

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2010 UPGrowthAnEfficientAlgorithmfor	Philip S. Yu Vincent S. Tseng Cheng-Wei Wu Bai-En Shie			UP-Growth: An Efficient Algorithm for High Utility Itemset Mining		KDD-2010 Proceedings	http://making.csie.ndhu.edu.tw/seminar/making/papers/PPT/UP-Growth An Efficient Algorithm for High Utility Itemset Mining(SIGKDD2010).pptx	10.1145/1835804.1835839		2010