Volume 6 Issue 3 - January 2016

  • 1. Mining high utility itemsets from large transactions using efficient tree structure

    Authors : Vinothini Thangamuthu

    Pages : 222-227

    Keywords : utility mining, pattern growth approach, high utility itemsets, systolic tree structure

    Abstract :

    Mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. It is an extension of the frequent pattern mining. Although a number of relevant algorithms 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. Association rule mining with item set frequencies are used to extract item set relationships. Frequent pattern mining algorithms are designed to find commonly occurring sets in databases. Memory and run time requirements are very high in frequent pattern mining algorithms. Systolic tree structure is a reconfigurable architecture used for utility pattern mining operations. High throughput and faster exec

    Citing this Journal Article :

    Vinothini Thangamuthu, "Mining high utility itemsets from large transactions using efficient tree structure", https://www.ijltet.org/journal_details.php?id=898&j_id=2845, Volume 6 Issue 3 - January 2016, 222-227, #ijltetorg