Over the last few years there has been a significant development in the e-learning industry that provides online courses to the public. Due to the drastic improvement in technology and the Internet, this form of education reaches many people across boundaries. There is vast set of courses currently provided by various sources, which range from the latest technologies in the field of computer science to any topic in history. Since the invention of e-learning, there has been constant improvement of user friendly tools to enhance the learning process. In the span of the last three years, many websites have come into existence that provide online courses. Some of the best universities in the United States and other universities throughout the world have also started to provide online courses that students can easily attend. It has become very difficult for a student to pick the right online course. Hence, an application that can integrate the courses provided by various e-learning websites like Coursera, Udacity and Edx would be very helpful. The student can compare the regular courses provided by his or her university with the courses offered by the e-learning websites and can enroll in similar online courses to get a better understanding of the subject. The objective of this project is to use semantic similarity techniques to identify the MOOCs [massive open online courses] offered by the e-learning websites which are similar to the regular courses offered by the university.
Tenali, Krishna Nitin, "SEMANTIC SIMILARITY BASED INFORMATION RETRIEVAL AS APPLIED TO MOOCs" (2014). Master's Projects. 340.