Development of Simultaneous Inclusion and Correlation Visualization System Using Formal Concept Analysis and Quantification Theory Class III

Yusei Shimada, Toshinobu Harada
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Abstract

: In recent years, while data mining has attracted attention, formal concept analysis has the disadvantage that although it can understand the inclusion relation between attributes, it doesn’t know what kind of meaning or inclusion relation the attributes have. Therefore, in this study, the inclusion of the attributes and the visualization of the correlation are realized by combining the Hasse diagram by formal concept analysis and the layout diagram of the attribute of quantification theory type III for visualizing the meaning between the attributes. Moreover, in order to confirm usefulness of the proposed method, we developed a simultaneous visualization system of inclusion and correlation combining formal concept analysis and quantification theory type III, and evaluated the proposed method using verification data. As a result, it was confirmed that useful information that can’t be obtained only by formal concept analysis or quantification theory type III can be extracted.
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利用形式化概念分析和量化理论开发同时包含和关联可视化系统(III)
近年来,在数据挖掘受到关注的同时,形式概念分析的缺点是虽然可以理解属性之间的包含关系,但不知道属性具有什么样的含义或包含关系。因此,在本研究中,通过形式化概念分析的Hasse图与量化理论III型属性布局图相结合,实现属性的包含与关联的可视化,实现属性之间意义的可视化。此外,为了验证所提方法的有效性,我们将形式概念分析与量化理论III型相结合,开发了包含与关联同步可视化系统,并使用验证数据对所提方法进行了评估。结果证实,可以提取出仅通过形式概念分析或量化理论III类无法获得的有用信息。
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