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An Efficient Recommendation System on E-Learning Platform by Query Lattice Optimization
S. Ghosh, S. Roy,
Published in Springer
Volume: 1174
Pages: 73 - 86
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. © 2021, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer