Data mining uses various techniques and theories from a wide range of areas for the knowledge extraction from large volumes of data. However, uncertainty is a widespread phenomenon in data mining problems. Accordingly, fuzzy logic is applied to cope with the uncertainty in real world.

The aim of this special issue has twofold: (i) to present recent outstanding developments and trends in the theory and algorithms of data mining using fuzzy logic and (ii) to create a multidisciplinary forum of discussion on recent advances in data mining as well as new applications to biology, economics, ecology, engineering, finance, management, medicine, and so on using fuzzy logic.

Since data mining technology is widely studied and applied in various areas of science, we invite all the related researchers from the fields of computer science, engineering, statistics, economy, finance, marketing, social sciences, healthcare, and so on.

Potential topics include, but are not limited to:

• Clustering
• Classification
• Support vector machines
• Neural networks
• Sequential data analysis
• Pattern recognition
• Machine learning
• Fuzzy statistics
• Real-world applications of data mining in finance, economics, engineering, biology, medicine, image processing, and so on