Quantitative Analytic Framework of Relations among Unstructured Data
Quantitative Analytic Framework of Relations among Unstructured Data
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DOI：
10.1109/smc42975.2020.9283067
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Takeru Yokoi;Ryota Ikushima;R. Ibrahim
中科院分区：
文献类型：
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作者：
Takeru Yokoi;Ryota Ikushima;R. Ibrahim
在最近的大数据中存在着各种各样的关系，对于理解海量信息非常重要。针对聚类算法中的误分类项，提出了一种非结构化数据间关系的分析框架。这个框架成功地找出了物质之间的某种关系。然而，分析框架只能对这些关系进行主观分析，而不能进行定量分析。因此，在本文中，我们开发了这些关系的定量分析框架。在之前的工作之后，我们还利用新闻文章进行了实验，并对国家之间的关系进行了定量分析。
Various relations exist in the recent big data and are important in understanding enormous information. We have proposed an analytic framework of relations among unstructured data focusing on miss-classified items in clustering algorithms. The framework has succeeded in finding out somewhat relations among substances. The analytical framework, however, could only perform the subjective analysis but quantitative analysis of those relations.In this paper, we, therefore, have developed the quantitative analytic framework of those relations. We also carried out experiments using news articles and quantitative analysis of the relations among nations following the previous work.