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| 基于极大团和FP-Tree的挖掘关联规则的改进算法 | |
| 引用本文： | 陈安龙,唐常杰,陶宏才,元昌安,谢方军.基于极大团和FP-Tree的挖掘关联规则的改进算法[J].软件学报,2004,15(8):1198-1207. |
| 作者姓名： | 陈安龙 唐常杰 陶宏才 元昌安 谢方军 |
| 作者单位： | 1. 四川大学,计算机学院,四川,成都,610064 2. 西南交通大学,计算机与通信工程学院,四川,成都,610031 3. 四川大学,计算机学院,四川,成都,610064;广西师范学院,信息技术系,广西,南宁,530001 |
| 基金项目： | Supported by the National Natural Science Foundation of China under Grant No.60073046 (国家自然科学基金); the National Research Foundation for the Doctoral Program of Higher Education of China under Grant No.20020610007 (国家教育部博士点专项基金); the Natural Science Foundation of Guangxi Province of China under Grant No.0339039 (广西自然科学基金) |
| 摘 要： | 融合了关联规则挖掘的FP-Tree算法和图论的极大团理论的优势,做了以下主要工作:(1) 提出了用邻接矩阵的产生频繁2-项集的改进方法;(2) 提出了极大有序频繁集的概念,证明了Head关系的等价性、划分定理、局部复杂性定理和归并收敛值域定理;(3) 提出并实现了基于极大团划分的MaxCFPTree算法,扫描时间复杂性小于O(n2);(4) 做了相关实验,以验证算法的正确性.新方法缓解了项目数量巨大而内存不足的矛盾,提高了系统效率和伸缩性. |
| 关 键 词： | 关联规则 FP-Tree 极大团 邻接矩阵 归并收敛 |
| 文章编号： | 1000-9825/2004/15(08)1198 |
| 收稿时间： | 2003/10/28 0:00:00 |
| 修稿时间： | 2003年10月28 |
An Improved Algorithm Based on Maximum Clique and FP-Tree for Mining Association Rules |
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| CHEN An-Long,TANG Chang-Jie,TAO Hong-Cai,YUAN Chang-An and XIE Fang-Jun.An Improved Algorithm Based on Maximum Clique and FP-Tree for Mining Association Rules[J].Journal of Software,2004,15(8):1198-1207. | |
| Authors: | CHEN An-Long TANG Chang-Jie TAO Hong-Cai YUAN Chang-An and XIE Fang-Jun |
| Abstract: | This paper integrates the advantage of the FP-Tree algorithm for mining association rules and the maximum clique theory of graph. The main contributions include: (1) An improved method to mine frequent 2-itemset by adjacency matrix is proposed. (2) The concept of maximum ordered frequent itemset is proposed, and the equivalence of Head Relation is proved as along with the theorems about Local Complexity and Merge Convergence Range. (3) The MaxCFPTree algorithm based on Maximum-clique partition is proposed and implemented with complexity O(n2). (4) The algorithms are validated by extensive experiments. The conflict between memory and huge number of items is resolved, and the system efficiency and scalability are improved. |
| Keywords: | association rules FP-tree maximum clique adjacency matrix merge convergence |
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