Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Pre-course student performance prediction with multi-instance multi-label learning

This is a preview of subscription content, log in to check access.

References

  1. 1

    Ren Z, Rangwala H, Johri A. Predicting performance on MOOC assessments using multi-regression models. In: Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, 2016. 484–489

  2. 2

    Meier Y, Xu J, Atan O, et al. Predicting grades. IEEE Trans Signal Process, 2016, 64: 959–972

  3. 3

    Zhou Z H, Zhang M L. Multi-instance multi-label learning with application to scene classification. In: Proceedings of International Conference on Neural Information Processing Systems, Vancouver, 2006. 1609–1616

  4. 4

    Zafra A, Romero C, Ventura S. Multiple instance learning for classifying students in learning management systems. Expert Syst Appl, 2011, 38: 15020–15031

  5. 5

    Sweeney M, Rangwala H, Lester J, et al. Next-term student performance prediction: a recommender systems approach. ArXiv: 1604.01840

  6. 6

    Zhang M L. A k-nearest neighbor based multi-instance multi-label learning algorithm. In: Proceedings of the 22nd International Conference on Tools with Artificial Intelligence (ICTAI’10), Arras, 2010. 207–212

  7. 7

    Chawla N V, Japkowicz N, Kotcz A. Editorial: special issue on learning from imbalanced data sets. ACM SIGKDD Explorations Newslett, 2004, 6: 1–6

  8. 8

    Wang J, Zucker J D. Solving the multiple-instance problem: a lazy learning approach. In: Proceedings of the 17th International Conference on Machine Learning, Stanford, 2000. 1119–1126

  9. 9

    Zhou Z H. Machine Learning. Beijing: Tsinghua University Press, 2016. 29–35

Download references

Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 61671274, 61573219, 61701281), Science and Technology Plan Project of Shandong Higher Education Institutions (Grant No. J15LN55), Shandong Provincial Natural Science Foundation (Grant No. ZR2017QF009), Fostering Project of Dominant Discipline and Talent Team of Shandong Province Higher Education Institutions, and China Postdoctoral Science Foundation (Grant No. 2016M592190).

Author information

Correspondence to Yilong Yin.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ma, Y., Cui, C., Nie, X. et al. Pre-course student performance prediction with multi-instance multi-label learning. Sci. China Inf. Sci. 62, 29101 (2019). https://doi.org/10.1007/s11432-017-9371-y

Download citation