基于范围关系的医疗数据频繁时态模式挖掘

2017 IEEE International Conference on Data Mining Workshops (ICDMW) Pub Date : 2017-11-01 DOI:10.1109/ICDMW.2017.87

S. Hirano, S. Tsumoto

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引用次数: 1

摘要

提出了一种医学数据的时态模式挖掘方法。它对Batal等人提出的挖掘算法进行了改进，纳入了范围关系。实验结果表明，该方法可以生成具有抽象时间范围的频繁模式。

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Frequent Temporal Pattern Mining for Medical Data Based on Ranged Relations

This paper presents a temporal pattern mining method for medical data. It modifies the mining algorithms proposed by Batal et al. to incorporate with ranged relations. Experimental results demonstrate that the proposed method could generate frequent patterns with abstracted time ranges embedded in their temporal relations.

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来源期刊

2017 IEEE International Conference on Data Mining Workshops (ICDMW)

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