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题名:
an efficient algorithm for mining erasable itemsets
作者: Deng Zhihong ; Xu Xiaoran
会议文集: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
会议名称: 6th International Conference on Advanced Data Mining and Applications, ADMA 2010
会议日期: 40848
出版日期: 2010
会议地点: Chongqing, China
关键词: Chemical industry ; Data mining
出版地: Germany
收录类别: ei
ISSN: 3029743
ISBN: 3642173152
部门归属: (1) Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China; (2) State Key Lab. of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
主办者: National Natural Science Foundation of China; Chongqing Science and Technology Commission; Chongqing Academy of Science and Technology
英文摘要: Mining erasable itemsets first introduced in 2009 is one of new emerging data mining tasks. In this paper, we present a new data representation called PID-list, which keeps track of the id-nums (identification number) of products that include an itemset. Based on PID-list, we propose a new algorithm called VME for mining erasable itemsets efficiently. The main advantage of VME algorithm is that the gain of an itemset can be computed efficiently via union operations on product id-nums. In addition, VME algorithm can also automatically prune irrelevant data. For evaluating VME algorithm, we have conducted experiments on six synthetic product databases. Our performance study shows that the VME algorithm is efficient and is on average over two orders of magnitude faster than the META algorithm, which is the first algorithm for dealing with the problem of erasable itemsets mining. © 2010 Springer-Verlag.
语种: 英语
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8650
Appears in Collections:中科院软件所图书馆_2010软件所会议论文

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Recommended Citation:
Deng Zhihong,Xu Xiaoran. an efficient algorithm for mining erasable itemsets[C]. 见:6th International Conference on Advanced Data Mining and Applications, ADMA 2010. Chongqing, China. 40848.
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