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ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2006, Vol. 7 Issue (2 ): 17-    DOI: 10.1631/jzus.2006.A0216
    
A novel algorithm for frequent itemset mining in data warehouses
Xu Li-jun, Xie Kang-lin
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200030, China
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Abstract  Current technology for frequent itemset mining mostly applies to the data stored in a single transaction database. This paper presents a novel algorithm MultiClose for frequent itemset mining in data warehouses. MultiClose respectively computes the results in single dimension tables and merges the results with a very efficient approach. Close itemsets technique is used to improve the performance of the algorithm. The authors propose an efficient implementation for star schemas in which their algorithm outperforms state-of-the-art single-table algorithms.

Key words： Frequent itemset      Close itemset      Star schema      Dimension table      Fact table     
Received: 11 June 2005     
CLC:  TP31  
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Xu Li-jun
Xie Kang-lin
Cite this article:

Xu Li-jun, Xie Kang-lin. A novel algorithm for frequent itemset mining in data warehouses. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2006, 7(2 ): 17-.

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http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.2006.A0216     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2006/V7/I2 /17

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