An Efficient Recommendation System on E-Learning Platform by Query Lattice Optimization

Abstract

This research work is on optimizing the number of query parameters required to recommend an e-learning platform. This paper proposes a new methodology for efficient implementation by forming lattice on query parameters. This lattice structure helps to co-relate the different query parameters that in turn form association rules among them. The proposed methodology is conceptualized on an e-learning platform with the objective of formulating an effective recommendation system to determine associations between various products offered by the e-learning platform by analyzing the minimum set of query parameters.