User Profiling Based Recommendation System for E-Learning

The current e-Learning management systems contain a huge pool of data gathered from multiple sources but main challenge that these systems are facing is the provision of relevant and quality content to the users and reduce the time wasted by the users to search this content. Also, with differences in the learning capabilities not all users can undertake the same learning track for understanding a particular content. In this paper, different user profiling methods, personalization methods and filtering techniques have been discussed and an approach has been presented to develop a web portal for adaptive e-learning. Furthermore, the paper discusses keyword focused web crawler to extract relevant information and use it further as a part of recommendation systems.