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)
AuthorsYuh-Jiuan Tsay, 蔡玉娟
出版日期2009 / 1

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.

期刊名稱Information Sciences
校址:912 屏東縣內埔鄉學府路1號 總機:886-8-7703202 傳真:886-8-7740165 系統開發統維護單位:國立屏東科技大學 電算中心 版權所有