Big data has become a significant research area due to the birth of enormous data
generated from various sources like social media, internet of things and multimedia …

Attribute reduction plays an important role in the areas of rough sets and granular
computing. Many kinds of attribute reducts have been defined in previous studies. However …

The amount of data collected from different real-world applications is increasing rapidly.
When the volume of data is too large to be loaded to memory, it may be impossible to …

Hierarchical classification is an important research hotspot in machine learning due to the
widespread existence of data with hierarchical class structures. The existing sequential …

Owing to the self-improvement desire, the human being always tries to reach to the current
information and generate new ones from the data on hand. The practices are realized by …

Three-way decisions provide a trisecting-and-acting framework for complex problem solving.
For a cost-sensitive decision-making problem under multiple levels of granularity, sequential …

Attribute reduction is nowadays an extremely important data preprocessing technique in the
field of data mining, which has gained much attention due to its ability to provide better …

A back-propagation (BP) neural network can solve complicated random nonlinear mapping
problems; therefore, it can be applied to a wide range of problems. However, as the sample …

Mining with big data or big data mining has become an active research area. It is very
difficult using current methodologies and data mining software tools for a single personal …

Three-way decisions have become a representative of trisecting-and-acting model for
uncertainty data analysis. With granular computing point of view, a more reasonable …