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Data Mining Framework for Treating both Numerical and Text Data

  • International Journal of Service and Knowledge Management
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Abstract

In recent years, data mining and text mining techniques have been frequently used for analyzing data. Electronic data is collected in everywhere and many products and services are widely used in our daily lives. 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 the text part cannot be connected for interpretation. Goal of the data analysis is knowledge emergence that we find or create a new knowledge for decision making.

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Publication details

DOI
10.52731/ijskm.v2.i1.229
OpenAlex
W2884348384
Document type
article
Language
EN
Source
International Journal of Service and Knowledge Management
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