基于本体的多维关联规则挖掘

H. Brahmi
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引用次数: 1

摘要

许多方法都提供了适用的解决方案来解释数据集中的关联。然而,仍然存在许多问题,导致用户额外的时间来获取真正的知识,甚至无法获得他们所需要的有用的知识。本文提出了一种基于本体的多维关联规则挖掘方法,该方法结合领域本体,帮助用户减少系统资源消耗,提高挖掘过程的效率。说明了该本体的结构,并说明了它对挖掘过程的好处。实验结果表明,与相同趋势下的拟合方法相比,本文提出的方法具有显著的改进和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ontology Enhanced Mining of Multidimensional Association Rules from Data Cubes
Many approaches have provided applicable solutions to explain associations within data cubes. Nevertheless, there are still many issues causing users extra time to get real knowledge or even failing to obtain the useful knowledge they need. In this paper, we introduce an ontology based approach for multidimensional association rule mining that incorporates a domain ontology to help users in reducing the system resource consumption and improving the efficiency of the mining process. The structure of this ontology is illustrated and how it would be of benefit to the mining process is also demonstrated. Our experimental results prove that a significant improvement and efficiency is achieved using our suggested approach in comparison with those fitting in the same trend.
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