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  Implementation of Student Psychology Prediction- Recommendation Two Phase Strategy  
  Authors : Bhakti Ratnaparkhi
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Big data analysis includes many theories and methods for prediction system. Statistical methods such as Person’s correlation, Regression analysis and Rough Set Theory etc are being used for predicting facts. Also theory like collaboration filtering uses word’s filtering to predict and provide recommendations. We have studied all these methods and selected most appropriate method for student’s psychology prediction. In our proposed work we have used Rough sets to extract the rules for prediction of student’s psychology. Rough Set is a comparatively recent method that has been effective in various fields such as medical, geological and other fields where intelligent decision making is required. Our experiments with rough sets in predicting student’s psychology produced attractive results.

 

Published In : IJCSN Journal Volume 5, Issue 5

Date of Publication : October 2016

Pages : 818-823

Figures :04

Tables :--

 

Bhakti Ratnaparkhi : Department of Information Technology, Pimpri Chinchwad College of Engineering, Pune.

 

 

 

 

 

 

 

Student’s Psychology, Prediction, Recommendation, Rough Set Theory

Various techniques used for prediction and recommender system were studied in order to develop system for prediction of student psychology and provide remedial actions to improve their academic performance with improved accuracy in prediction and recommender system. Maslow motivation theory was also studied which will be used for predicting current state of student’s psychology and also to provide suggestions for improvements. Our own 2-phase model was proposed and results were obtained through simulation.

 

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