Ontology driven environment for semantic learning

Abstract

Ontology Driven environment for Semantic Learning is semantic learning software which is capable of learning from a natural language source. It identifies language complexity, ambiguity and influence of diverse writing styles to extract and decipher. The specialty here in the system is usage of its acquired knowledge to perform teaching and explaining activities to its end users.Simply it learns somewhat like a human and teaches what it has learnt as a human does. Several efforts have been made over the last two decades to build computer software which is capable of learning from the natural language sources, understanding the learnt content, representing the knowledge and self-explaining. The technology of natural language processing is still in controlled manner with inability of processing the complete natural language and ignoring the language complexity, ambiguity and different written patterns. Most of them have not focused on building a framework with learning, Knowledge representation and teaching capabilities and also they were not able to ignore the human enrolment oflimitations when extracting the actual meaning of the learning process. That indicates, still the machine needs more human assistance in learning. This was one of the major hallucinations of the field of artificial intelligence which is still a miracle. This thesis is meant to delineate the background, research review, functions and features of Ontology Driven Semantic Self Learning and Teaching Framework. It further explained the purpose, literature, the interfaces, evaluation ofthe research, the constraints under which it must operate, conclusion and benefits ofthe research and how the system reacts to external stimuli. The software is endowed with inventions involving in Natural Language Processing, machine learning, explanation and knowledge representation and ontology, which are still under research.