FIUT: A new method for mining frequent itemsets

in Sciences Citation Index(SCI), 科學引文索引資料庫(SCI)
標題FIUT: A new method for mining frequent itemsets
出版類型SCI(Sciences Citation Index)
出版年度2009
AuthorsYuh-Jiuan Tsay, 蔡玉娟
開始頁1724
頁數13
出版日期2009 / 1
其他編號0000
中文摘要

This paper proposes an efficient method, the frequent items ultrametric trees (FIUT), for mining frequent itemsets in a database. FIUT uses a special frequent items ultrametric tree (FIU-tree) structure to enhance its efficiency in obtaining frequent itemsets. Compared to related work, FIUT has four major advantages. First, it minimizes I/O overhead by scanning the database only twice. Second, the FIU-tree is an improved way to partition a database, which results from clustering transactions, and significantly reduces the search space. Third, only frequent items in each transaction are inserted as nodes into the FIU-tree for compressed storage. Finally, all frequent itemsets are generated by checking the leaves of each FIU-tree, without traversing the tree recursively, which significantly reduces computing time. FIUT was compared with FP-growth, a well-known and widely used algorithm, and the simulation results showed that the FIUT outperforms the FP-growth. In addition, further extensions of this approach and their implications are discussed.

網址http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V0C-4VDS8JY-1&_user=2535637&_coverDate=05%2F13%2F2009&_alid=1250846815&_rdoc=1&_fmt=high&_orig=search&_cdi=5643&_sort=r&_docanchor=&view=c&_ct=4&amp
期刊名稱Information Sciences
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