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.
