Knowledge network model with neurocognitive processing capabilities

Abstract

The prime focus of scientists and the researchers in the field of intelligent systems is oriented to understand and replicate information processing functionalities of the human brain network. There have been continuous efforts to develop an intelligent knowledge system that incorporates the neuronal processes involved in cognition. In this paper the authors give some details of their unique work on the development of a knowledge system with information processing functionalities moving toward cognitive processing of the human brain, using intelligent links and nodes with processing capabilities. The existing knowledge systems connect only the pieces of information represented by nodes of a network and connect nodes using connectors, referred as edges. The edge is an attribute defining a relationship (e.g. isA, hasA) between the nodes. These edges lack cognitive properties, and the nodes lack functional processing to support efficient information transfer between nodes. The main objective of this paper is to provide an overview of the characteristics of a neurocognitive knowledge network model (NCKM) developed by the authors. NCKM is a knowledge network with nodes and links developed to provide methods that deal with the cognitive processes of the human brain, useful for efficient information processing. These cognitive processes provide self-directivity and learning within the network for intelligent knowledge retrieval. This work opens up a pathway to ingrain cognitive and neuronal characteristics for information processing into knowledge networks.