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Mining over a Reliable Evidential Database: Application on Amphiphilic Chemical Database

机译:在可靠的证据数据库上进行挖掘:在两亲化学数据库上的应用

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In recent years, the mining of frequent itemsets from uncertain databases has attracted much attention. Several researches have been conducted using different uncertain frameworks as probabilities, fuzzy sets and, most recently, evidence theory. There is very little study paid to mining pertinent knowledge from data where reliability is questionable. In this paper, we study and extend the evidential database framework in accounting data reliability. We propose new measures of support and confidence under uncertainty that consider the reliability and extend the state-of-the-art works. The proposed framework is thoroughly experimented on a real case problem for developing classification model from a chemical database.
机译:近年来,来自不确定数据库的频繁项集的挖掘已引起了广泛的关注。使用不同的不确定性框架(如概率,模糊集以及最近的证据理论)进行了数项研究。对于从可靠性值得怀疑的数据中挖掘相关知识的研究很少。在本文中,我们研究并扩展了会计数据可靠性方面的证据数据库框架。我们提出了在不确定性下支持和置信度的新措施,这些措施考虑了可靠性并扩展了最新技术。在从化学数据库开发分类模型的实际案例问题上,对提出的框架进行了充分的实验。

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