A knowledge base stores facts and rules about the world that applications can use for the purpose of reasoning. By applying the concept of granular computing to a knowledge base, several advantages emerge. These can be harnessed by applications to improve their capabilities and performance. In this paper, the concept behind such a construct, called a granular knowledge cube, is defined, and its...

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.

We propose a higher order logic called as the granular logic. This logic is introduced as a tool for investigating properties of granular computing. In particular, constants of this logic are of the form m(F ), where F is a formula (e.g., Boolean combination of descriptors) in a given information system. Truth values of the granular formula are discussed. The truth value of a given formula in a...

A simple and more concrete granular computing model may be developed using the notion of information tables. In this framework, each object in a finite nonempty universe is described by a finite set of attributes. Based on attribute values of objects, one may decompose the universe into parts called granules. Objects in each granule share the same or similar description in terms of their attrib...

This paper introduces a new framework for privacy preserving computation to the granular computing community. The framework is called P4P (Peers for Privacy) and features a unique architecture and practical protocols for user data validation and vector addition-based computation. It turned out that many non-trivial and non-linear computations can be done using an iterative algorithm with vector...

Granular Computing is an emerging conceptual and computing paradigm of information processing. A central notion is an information-processing pyramid with different levels of clarifications. Each level is usually represented by ‘chunks’ of data or granules, also known as information granules. Rough Set Theory is one of the most widely used methodologies for handling or defining granules. Ontolog...

This paper initially analyzes the methods of four attack types, including Probing, DoS (Denial of Service), R2L (Remote to Local) and U2R (User to Root). It then categorizes attacks into four cases which are, respectively, one host-one host, one host-many hosts, many hosts-one host and many hosts-many hosts. Categorization is based on resource and destination addresses of network packages. Gran...

Granular neural networks(GNNs) as a new calculation system structure based on Granular Computing(GrC) and artificial neural network can be able to deal with all kinds of granular information of the real world. This article has made the summary on the development and the present situation of GNNs. Firstly, it introduces the basic model of GrC: word calculation model based on fuzzy sets theory, r...

Granular computing aims to develop a granular view for interpreting and solving problems. The model of neighborhood rough sets is one of effective tools for granular computing. This model can deal with complex tasks of classification learning. Despite the success of the neighborhood model in attribute reduction and rule learning, it still suffers from the issue of granularity selection. Namely,...