Improvement of e-learning in Ontology using Machine Learning Techniques

E-learning is a way of delivering the knowledge to the learners through mobile, tabs and computer. Basically, eLearning is directed on the Internet, where learners can access their learning materials online at any time and any place. In this paper, machine learning approach goals are to deliver individualized, dynamic learning performance, supporting the improvement of knowledge. It is significant for thinking on accessible knowledge. Ontology is concerned with what is real or truth and the nature of genuineness and reality. The utilization of ontology method is to demonstrate the knowledge on certain areas. E-learning ontology can be used for representing domains in educational fields and for describing vibrant knowledge. This work contributes an balanced way for dealing with an educative model by consolidating ontology advancement. The following steps adapted for Ontology advancement are defining the domain and scope of the ontology, considering reprocessing present ontology, Enumerate significant terms. The main principal issues of educational fields are the absence of control data designing area through e-Learning performers. Building modelling helps in communication between the structure and behavior of the e-learning system. E-learning ontology has the ability to define a semantic model of the data combined with the domain knowledge. The proposed Enhancement of e-learning ontology using machine learning approach disclosure technique has been truthfully tried in an e-Learning environment for showing the subject Database Management Systems. In this proposed system student is going to select his subjects and he should take the test of that particular subject then by seeing his obtained marks in that subject its asks whether he needs pdf's or video in his feedback form then by predicting his performance it shows the particular videos or pdf's. The main intension of this paper is to exploit the KNN, SVM and K-Means algorithms for clustering of students and to utilize the ontology idea of comprehension and learning style recognizable identification.