• Shubhangi S. Tambe Student, Department Of Computer, JSPM NTC, India
  • Prof. Ganesh V. Kadam Professor, Department Of Computer, JSPM NTC, India


Ontology Reasoning, Fuzzy Logic, M-Tree, TF-IDF, Pearson Correlation


E- learning systems are becoming increasingly popular in educational establishments due to the development of web-based information and communication technologies. Most of the fact that many of the recommendation system are providing recommendation for the fired query. But very few are recommending by having continuous stream of exercises for the user to guide them properly.  E-learning is being developed to allow educators to assess on-line learning activities. Most data mining algorithms require specific parameters and threshold values to tune the process of discovery, the web usage mining applications of users   in the context of e-learning, educators and e-learning site designers. To enhance the process of the recommendation in E learning sector proposed system provides a better way of managing the users query to narrow down the student option to help to select his best course using fuzzy logic which powered with ontology and Tree hierarchy. So proposed methodology put forwards an idea of E learning system by M tree hierarchy which is powered with ontology for semantic relationship by using fuzzy logic.


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How to Cite

Shubhangi S. Tambe, & Prof. Ganesh V. Kadam. (2016). ENHANCING A FRAMEWORK FOR E-LEARNING SYSTEM USING ONTOLOGY AND FUZZY TREE MATCHING . International Education and Research Journal (IERJ), 2(1). Retrieved from https://ierj.in/journal/index.php/ierj/article/view/86