Research on Elementary School Students’ Books Recommendation Algorithm Based on Words and Character Library
Yufeng Chen, Jun Ma, Yaqiong Du, Rui Qi Sun, Bojuan Niu · 2021
There are many book recommendation systems, but there are few recommendation systems for Chinese elementary school students. Children's cognitive models are very different from adults, the personalized and accurate recommendation algorithm for them needs to be recommended based on the knowledge structure of children at different ages. In the paper, a new framework model of classified books for Chinese elementary school students was proposed. First of all, a words library and a character library are extracted from six grades textbooks, which named as B_W and B_C respectively; secondly, four machine learning methods are used for prediction, through the indicator of ACC, Recall and F1-Scores, iRF has the best performance in four methods, the max ACC of iRF is 95.3%, which is 10 percentage points better than NB method.