Ontological solution for enabling continuous learning

Abstract

Human being starts the learning process with a minimal knowledge and then constructs the knowledge by adding new contents or updating the existing knowledge. The research ‘Ontological solution for enabling Continuous Learning’ provides an approach, which can learn and expand the knowledge somewhatsimilarto a human being. Human knowledge is constructed by gathering totally new concepts or expanding the already existing content. People have identified the importance of intelligent machines which can learn and behave as human beings. Intelligent and advanced systems have become popular with the development and rapid changes of the technology. Knowledge representation and updating can be defined as a most crucial requirement in intelligent systems. Knowledge management researches focus on the development of concepts, methods, and tools supporting the management of human knowledge. In most of the intelligent systems, knowledge representation and knowledge updating processes are done by a human expert and there is no proper way to represent and update knowledge in an automated way without human involvement. Knowledge representation via ontology can be introduced as a most popular approach to represent and manipulate knowledge. ‘Ontological solution for enabling Continuous Learning’ can be defined as an automated knowledge acquisition mechanism by constructing ontology and integrating two or more ontology. The research reveals a mechanism to update the existent knowledge by comparing and integrating new knowledge. This thesis is meant to delineate the background, research review, functions and features ofthe research. It further explained the purpose, literature, approach, methodology, evaluation of the research, the constraints under which it must operate, conclusion and benefits of the research. The software is endowed with inventions involving in knowledge representation via ontology, which are still under research. Knowledge extraction, knowledge comparison, knowledge representation and knowledge integration can be defined as the main functions of the system. This solution can be used as the main learning process of any application and the knowledge will be easily manipulated in any intelligent system by embedding this ontology based solution.