FIUT: A new method for mining frequent itemsets 

[[abstract]]This paper proposes an efficient method, the frequent items ultrametric trees (FIUT), for mining frequent itemsets in a database. RUT 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 110 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. (C) 2009 Elsevier Inc. All rights reserved.[[note]]SC