| 基于基集与概念格的关联规则挖掘算法 |
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| 引用本文： | 陈湘,吴跃.基于基集与概念格的关联规则挖掘算法[J].计算机工程,2010,36(19):34-36. |
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| 作者姓名： | 陈湘 吴跃 |
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| 作者单位： | 电子科技大学计算机科学与工程学院,成都,610054 |
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| 基金项目： | 国家自然科学基金资助项目"基于神经网络的大规模数值模拟数据分析技术与研究" |
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| 摘 要： | 传统关联规则挖掘算法的挖掘效率较低，且挖掘结果中存在大量冗余。针对该问题，提出一种基于概念格与基集的关联规则挖掘算法。利用规定种子项分布范围的基集代替原始数据库以缩小挖掘源规模，从而建立概念格快速求解出关联规则。实验结果表明，该算法在时间效率方面优于Base和Apriori算法。
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| 关 键 词： | 数据挖掘 关联规则 概念格 基集 |
Association Rule Mining Algorithm Based on Base Set and Concept Lattice |
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| CHEN Xiang,WU Yue.Association Rule Mining Algorithm Based on Base Set and Concept Lattice[J].Computer Engineering,2010,36(19):34-36. |
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| Authors: | CHEN Xiang WU Yue |
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| Affiliation: | (School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China) |
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| Abstract: | Traditional association rule mining algorithm has low efficiency and it has a mount of redundant in mining results. Aiming at this problem, this paper presents an association rule mining algorithm based on base set and concept lattice. It replaces the original database with the base set which has seed item distribution range, and builds concept lattice to find association rules. Experimental results show that this algorithm has much superior to Base and Apriori algorithm on the performance of time efficiency. |
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| Keywords: | data mining association rule concept lattice base set |
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