Open AccessA Top-N Algorithm-based Personalized Learning Recommendation System for Digital Library
Author(s) -
Xin Gao,
Wenxue Huang,
Ning Wang,
Yanchao Yang,
Ying Yan
Publication year - 2016
Publication title -
international journal of emerging technologies in learning (ijet)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 24
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v11i11.6256
Subject(s) - diversification (marketing strategy) , computer science , recommender system , key (lock) , digital library , algorithm , machine learning , data mining , world wide web , art , poetry , literature , business , computer security , marketing
The digital library brings convenience, but meanwhile, it also brings the problems of overloaded information and over-diversified forms,thus search becomes difficult. Personalized Learning Recommendation System is the key to solve the problems, and suitable for the situation with user diversification and demand diversification. With the System, users spend the least time and energy in accurately finding the information they need, where efficiency is improved to the greatest extent. The research conclusion of personalized learning recommendation system based on Top-N algorithm is based on the calculation of the experimental results from the analysis of the related theory and technology based on Top-N algorithm.
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