2015 | OriginalPaper | Chapter
e-Learning Recommender System for Teachers using Opinion Mining
Authors : Anand Shanker Tewari, Anita Saroj, Asim Gopal Barman
Published in: Information Science and Applications
Publisher: Springer Berlin Heidelberg
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In recent few years e-learning has evolved as one of the better alternative of the classroom approach. e-learning has crossed the geographical boundaries and now it is in the reach of every learner who is using internet. But merely presence of the e-learning websites does not make sure that all the content is very effective for the learners. Generally for learning any subject the learner has to traverse many websites for various topics because no single website provide all the best content about the subject at a single place. So we have to analyze the learner’s reviews about the website subject content in order to deliver all the best content at a single place. In this paper we proposed a new e-learning recommender system named as A
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. It analyzes the learner’s opinions about the subject contents and recommends the teachers, who have uploaded the tutorial on to the website to change the particular portion of the subject topic which is difficult to understand by the learners using opinion mining, not the complete topic. By this system after some time all the best content about the subject will be available at the single place.