Data Analysis Support by Combining Data Mining and Text Mining

被引:7
|
作者
Matsumoto, Tomoya [1 ]
Sunayama, Wataru [1 ]
Hatanaka, Yuji [1 ]
Ogohara, Kazunori [1 ]
机构
[1] Univ Shiga Prefecture, Sch Engn, 2500 Hassaka Cho, Hikone, Shiga 5228533, Japan
关键词
text mining; data mining; data analysis support; TETDM;
D O I
10.1109/IIAI-AAI.2017.165
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, data mining and text mining techniques have been frequently used for analyzing questionnaire and review data. Data mining techniques such as association analysis and cluster analysis are used for marketing analysis, because those can discover relationships and rules hiding in enormous numerical data. On the other hand, text mining techniques such as keywords extraction and opinion extraction are used for questionnaire or review text analysis, because those can support us to investigate consumers' opinion in text data. However, data mining tools and text mining tools cannot be used in a single environment. Therefore, a data which has both numerical and text data is not well analyzed because the numerical part and text part cannot be connected for interpretation. In this paper, a mining framework that can treat both numerical and text data is proposed. We can iterate data shrink and data analysis with both numerical and text analysis tools in the unique framework. Based on experimental results, the proposed system was effectively used to data analysis for review texts.
引用
收藏
页码:313 / 318
页数:6
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