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�������պ����ѧѧ�� 2009, Vol. 35 Issue (5) :640-643    DOI:
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Effective algorithm for mining compressed frequent patterns
Tong Yongxin1, Ma Shilong2, Li Yu2*
1. School of Software, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. School of Computer Science and Technology, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

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Abstract�� Researches of frequent-pattern mining have recently focused on discovering representative patterns to compress a large of results within a reasonable tolerance bound. A novel heuristic algorithm, approximating mining based simulated annealing (AMSA), was proposed. The algorithm uses a method based simulated-annealing to improve efficiency and quality of the compression. Our experimental studies demonstrate the algorithm is efficient and high quality on a common dataset supported by frequent itemset mining implementations repository (FIMI). The mining result of AMSA is smaller than mining results of FPclose and RPglobal by performance study. Especially, if min_sup threshold is low, RPglobal fails to generate any result within reasonable time range, while AMSA generates a concise and succinct mining result.
Keywords�� data mining   simulated annealing   heuristic method     
Received 2008-08-10;


About author: ͯӽ�(1982-),��,������,˶ʿ��,yxtong@nlsde.buaa.edu.cn.
ͯӽ�, ������, �� ��.һ����Чѹ��Ƶ��ģʽ�ھ���㷨[J]  �������պ����ѧѧ��, 2009,V35(5): 640-643
Tong Yongxin, Ma Shilong, Li Yu.Effective algorithm for mining compressed frequent patterns[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2009,V35(5): 640-643
http://bhxb.buaa.edu.cn//CN/     ��     http://bhxb.buaa.edu.cn//CN/Y2009/V35/I5/640
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