A Recommendation System for Prediction of Elective Subjects

Abstract

Besides recommending courses which are compulsory for every student to be taken, universities as well as autonomous colleges also offer elective courses selected by the students themselves. At an undergraduate level some students find it difficult to make the choice of elective subjects. By using the information of the past courses taken by the student it is possible to guide the student about elective courses correct for him/her, based on experiences of the other students. In this paper we model the past students performance in elective in relation to other courses taken in past and recommend student on the basis of this model.

Authors and Affiliations

Neha Bhagwan Samrit, Prof. A. Thomas

Keywords

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  • EP ID EP23714
  • DOI http://doi.org/10.22214/ijraset.2017.4007
  • Views 338
  • Downloads 6

How To Cite

Neha Bhagwan Samrit, Prof. A. Thomas (2017). A Recommendation System for Prediction of Elective Subjects. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(4), -. https://europub.co.uk/articles/-A-23714