Computer Science ›› 2017, Vol. 44 ›› Issue (10): 265-268.doi: 10.11896/j.issn.1002-137X.2017.10.048

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Cognitive Modeling Based on Binary Matrix Factorization

ZHANG Meng, FU Li-hua, HE Ting-ting and YANG Qing   

  • Online:2018-12-01 Published:2018-12-01

Abstract: A novel logistic binary matrix factorization (LBMF) was proposed to predict the students’ performance and to classify the exam items.Besides a new algorithm was designed to tackle the non-convex optimization problem involved in LBMF.The experiments are performed on both simulated data and real data.The results indicate that LBMF can not only predict the students’ academic performance but also classify the examination items according to the know-ledge points they require.And it can be concluded that LBMF outperforms significantly the out-of-date algorithms in the applications.

Key words: Cognitive modeling,Binary matrix factorization,Item classification,Student performance prediction

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