LCGMiner:从大型数据库中分层封闭图形模式挖掘

Proceedings. 16th International Conference on Scientific and Statistical Database Management, 2004. Pub Date : 2004-06-21 DOI:10.1109/SSDBM.2004.47

Aihua Xu, H. Lei

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引用次数: 3

摘要

LCGMiner (levelwise closed graph pattern miner)是为了改进CloseGraph (Yan and Han, 2003)在发现频繁闭子图方面的能力而提出的。与传统方法相比，具有相同扩展顶点集的频繁闭边集在模式生成中得到了扩展。在合成数据集和真实NIH数据集上的实验表明，我们的算法优于CloseGraph和gSpan。

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LCGMiner: levelwise closed graph pattern mining from large databases

LCGMiner (levelwise closed graph pattern miner) is proposed to improve CloseGraph (Yan and Han, 2003) in discovering frequent closed sub graphs. Frequent closed edgesets with the same extended vertexsets are expanded in pattern generation compared to one edge or one vertex in traditional methods. Experiments on synthetic datasets as well as a real NIH dataset demonstrates that our algorithm outperforms CloseGraph and gSpan.

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Proceedings. 16th International Conference on Scientific and Statistical Database Management, 2004.

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