Application of the Latest Data Mining Technology for Sustainability

Dear Colleagues,

With the advent of new technologies such as mobile technology, IoT, and sensors due to the advancement of ICT technology, organizations are faced with an environment where they create and use huge amounts and various types of big data.

While traditional data analysis focused on hypothesis verification based on deriving correlations between structured data, in the era of big data, the procedure of discovering and verifying hypotheses taking into account not only structured data but also unstructured data is becoming more common.

Data mining technology is drawing attention as the most useful tool for such big data analysis, and in particular, new technology based on deep learning is being developed at a rapid pace. New data mining technologies can be applied to various fields for providing keys to settle problems that humans could not solve and are recognized as important in academia and industry.

Therefore, data mining technology has become an essential element in securing sustainable competitiveness for various stakeholders and is an interesting subject to many researchers.

This Special Issue covers an approach to creative analytical models and generating innovative results through big data analysis based on new data mining technologies.

Topics of interest for this Special Issue include (but are not limited to):

- Artificial intelligence for sustainability;

- Business intelligence;

- Customer big data analytics;

- Data mining approach in healthcare;

- Data mining and forensic science;

- Deep learning for image recognition;

- Image reconstruction technology with deep learning;

- Machine learning for financial market prediction;

- Novel methods for big data analytics;

- Text mining application.

Prof. Dr. Jae Joon Ahn
Dr. Sukjun Lee
Prof. Dr. Jaeyun Kim
Guest Editors

Manuscript Submission Information

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• artificial intelligence
• big data analytics
• data mining
• deep learning
• machine learning
• sustainability
• text mining