Granular computing with multiple granular layers for brain big data processing

Granular computing for data mining

Granular computing, as an emerging research field, provides a conceptual framework for studying many issues in data mining. This paper examines some of those issues, including data and knowledge representation and processing. It is demonstrated that one of the fundamental tasks of data mining is searching for the right level of granularity in data and knowledge representation.

Data science, big data and granular mining

With the evolution of various modern technologies, huge amount f data is being constantly generated and collected around us. We re in the midst of what is popularly called information revolution nd are living in a so-called world of knowledge. Intentionally and/or ccidentally, generation of these data is inevitable. As a result, large ata, broadly characterised by three Vs – large volume, veloc...

Data science, big data and granular mining

On Modeling Data Mining with Granular Computing

The main objective of this paper is to advocate for formal and mathematical modeling of data mining, which unfortunately has not received much attention. A framework is proposed for rule mining based on granular computing. It is developed in the Tarski’s style through the notions of a model and satisfiability. The model is a database consisting of a finite set of objects described by a finite s...

Granular Computing in Image Processing and Understanding

Granular Computing (GrC) can be considered as a common name of theories, methodologies, techniques, and tools that make use of granules, i.e. groups, classes, or clusters of a universe, in the process of problems solving. Basic ideas of crisp information granulation have appeared in related fields, such as interval analysis, rough set theory, Dempster-Shafer theory of belief functions, cluster ...