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  • 标题:Improving Efficiency of Incremental Mining by Trie Structure and Pre-Large Itemsets
  • 其他标题:Improving Efficiency of Incremental Mining by Trie Structure and Pre-Large Itemsets
  • 作者:Le, Thien-Phuong ; Vo, Bay ; Hong, Tzung-Pei
  • 期刊名称:COMPUTING AND INFORMATICS
  • 印刷版ISSN:1335-9150
  • 出版年度:2014
  • 卷号:33
  • 期号:3
  • 页码:609-632
  • 语种:English
  • 出版社:COMPUTING AND INFORMATICS
  • 摘要:Incremental data mining has been discussed widely in recent years, as it has many practical applications, and various incremental mining algorithms have been proposed. Hong et al. proposed an efficient incremental mining algorithm for handling newly inserted transactions by using the concept of pre-large itemsets. The algorithm aimed to reduce the need to rescan the original database and also cut maintenance costs. Recently, Lin et al. proposed the Pre-FUFP algorithm to handle new transactions more efficiently, and make it easier to update the FP-tree. However, frequent itemsets must be mined from the FP-growth algorithm. In this paper, we propose a Pre-FUT algorithm (Fast-Update algorithm using the Trie data structure and the concept of pre-large itemsets), which not only builds and updates the trie structure when new transactions are inserted, but also mines all the frequent itemsets easily from the tree. Experimental results show the good performance of the proposed algorithm.
  • 关键词:Data mining; frequent itemset; incremental mining; pre-large itemset; trie
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