Dien, Tran Thanh, Thanh-Hai, Nguyen and Thai-Nghe, Nguyen. "Novel Approaches for Searching and Recommending Learning Resources" Cybernetics and Information Technologies, vol.23, no.2, 2023, pp.151-169. https://doi.org/10.2478/cait-2023-0019 (Scopus, Q2, ESCI)
L. -D. Quach, K. N. Quoc, A. N. Quynh, N. Thai-Nghe and T. G. Nguyen, "Explainable Deep Learning Models With Gradient-Weighted Class Activation Mapping for Smart Agriculture," in IEEE Access, vol. 11, pp. 83752-83762, 2023, doi: 10.1109/ACCESS.2023.3296792. (Scopus, Q1, SCIE)
Thai-Nghe, N., Xuyen, N.T.K., Tran, A.C., Dien, T.T. (2023). Dealing with New User Problem Using Content-Based Deep Matrix Factorization. In: Fujita, H., Wang, Y., Xiao, Y., Moonis, A. (eds) Advances and Trends in Artificial Intelligence. Theory and Applications. IEA/AIE 2023. Lecture Notes in Computer Science(), vol 13926. Springer, Cham. https://doi.org/10.1007/978-3-031-36822-6_16
Tran, A.C., Tran, DT., Thai-Nghe, N., Dien, T.T., Nguyen, H.T. (2023). Course Recommendation Based on Graph Convolutional Neural Network. In: Fujita, H., Wang, Y., Xiao, Y., Moonis, A. (eds) Advances and Trends in Artificial Intelligence. Theory and Applications. IEA/AIE 2023. Lecture Notes in Computer Science(), vol 13925. Springer, Cham. https://doi.org/10.1007/978-3-031-36819-6_20
Huynh-Ly, T.-N., Le, H.-T., & Thai-Nghe, N. (2023). Deep Biased Matrix Factorization for Student Performance Prediction. EAI Endorsed Transactions on Context-Aware Systems and Applications, 9(1), e4. https://doi.org/10.4108/eetcasa.v9i1.3147
Van-Quoc, V., Thai-Nghe, N. (2023). Skin Diseases Detection with Transfer Learning. In: Saraswat, M., Chowdhury, C., Kumar Mandal, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications. Lecture Notes in Networks and Systems, vol 551. Springer, Singapore. https://doi.org/10.1007/978-981-19-6631-6_11
Quach, LD., Quynh, A.N., Quoc, K.N., Thai, N.N. (2023). Using Optimization Algorithm to Improve the Accuracy of the CNN Model on the Rice Leaf Disease Dataset. In: So-In, C., Londhe, N.D., Bhatt, N., Kitsing, M. (eds) Information Systems for Intelligent Systems . Smart Innovation, Systems and Technologies, vol 324. Springer, Singapore. https://doi.org/10.1007/978-981-19-7447-2_47
Thai-Nghe, N., Thanh-Hai, N., Dien, T.T. (2022). Recommendations in E-Commerce Systems Based on Deep Matrix Factorization. In: Dang, T.K., Küng, J., Chung, T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2022. Communications in Computer and Information Science, vol 1688. Springer, Singapore. https://doi.org/10.1007/978-981-19-8069-5_28
Jodłowiec, M., Albu, A., Wołk, K., Thai-Nghe, N., Karasiński, A. (2022). Layer-Wise Optimization of Contextual Neural Networks with Dynamic Field of Aggregation. In: Nguyen, N.T., Tran, T.K., Tukayev, U., Hong, TP., Trawiński, B., Szczerbicki, E. (eds) Intelligent Information and Database Systems. ACIIDS 2022. Lecture Notes in Computer Science(), vol 13758. Springer, Cham. https://doi.org/10.1007/978-3-031-21967-2_25
Nguyen, H.T., Le, A.D., Thai-Nghe, N., Dien, T.T. (2022). An Approach for Similarity Vietnamese Documents Detection from English Documents. In: Dang, T.K., Küng, J., Chung, T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2022. Communications in Computer and Information Science, vol 1688. Springer, Singapore. https://doi.org/10.1007/978-981-19-8069-5_39
Thanh Nguyen, H., Kieu Nguyen, T., Tri Pham, M., Le Hoang Tran, C., Thanh Dien, T., Thai-Nghe, N. (2023). Similar Vietnamese Document Detection in Online Assignment Submission System. In: Phuong, N.H., Kreinovich, V. (eds) Biomedical and Other Applications of Soft Computing. Studies in Computational Intelligence, vol 1045. Springer, Cham. https://doi.org/10.1007/978-3-031-08580-2_23
Thai-Nghe, N., Sang, P.H. (2022). A Session-Based Recommender System for Learning Resources. In: Dang, T.K., Küng, J., Chung, T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2022. Communications in Computer and Information Science, vol 1688. Springer, Singapore. https://doi.org/10.1007/978-981-19-8069-5_51
Tran Thanh Dien, Nguyen Thanh-Hai and Nguyen Thai-Nghe. (2022). An approach for learning resource recommendation using deep matrix factorization (extended work), pp. 1-18, Journal of Information and Telecommunication, Taylor & Francis. 2022. DOI: 10.1080/24751839.2022.2058250 (ESCI)
Huynh Thanh-Du, Maciej Huk, Nguyen Hung Dung, Nguyen Thai-Nghe. (2022). An Attendance Checking System on Mobile Devices Using Transfer Learning. Pages 499 – 506, Volume 355: New Trends in Intelligent Software Methodologies, Tools and Techniques. Frontiers in Artificial Intelligence and Applications. IOS Press. DOI: 10.3233/FAIA220279
Nguyen Van-Binh and Nguyen Thai-Nghe (2022). Cardiovascular Disease Detection on X-Ray Images with Transfer Learning. In: Fujita, H., Fournier-Viger, P., Ali, M., Wang, Y. (eds) Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence. IEA/AIE 2022. Lecture Notes in Computer Science(), vol 13343. Springer, Cham. https://doi.org/10.1007/978-3-031-08530-7_15
Nguyen Thai-Nghe, Thanh-Tri Ngo and Huu-Hoa Nguyen. (2022). Deep Learning for Rice Leaf Disease Detection in Smart Agriculture. In: Dang, N.H.T., Zhang, YD., Tavares, J.M.R.S., Chen, BH. (eds) Artificial Intelligence in Data and Big Data Processing. ICABDE 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 124. Springer, Cham. https://doi.org/10.1007/978-3-030-97610-1_52
Thanh-Nhan Huynh-Ly, Huy-Thap Le and Nguyen Thai-Nghe. (2021). Integrating Deep Learning Architecture into Matrix Factorization for Student Performance Prediction. In: Dang T.K., Küng J., Chung T.M., Takizawa M. (eds) Future Data and Security Engineering. FDSE 2021. Lecture Notes in Computer Science, vol 13076. Springer, Cham. https://doi.org/10.1007/978-3-030-91387-8_26
Tran Thanh Dien, Pham Huu Phuoc, Nguyen Thanh-Hai and Nguyen Thai-Nghe . (2021). Personalized Student Performance Prediction Using Multivariate Long Short-Term Memory. In: Dang T.K., Küng J., Chung T.M., Takizawa M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2021. Communications in Computer and Information Science, vol 1500. Springer, Singapore. https://doi.org/10.1007/978-981-16-8062-5_16
Huong Thu Thi Luong, Huong Hoang Luong, Nguyen Thanh-Hai and Nguyen Thai-Nghe. (2021). Hospital Revenue Forecast Using Multivariate and Univariate Long Short-Term Memories. In: Dang T.K., Küng J., Chung T.M., Takizawa M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2021. Communications in Computer and Information Science, vol 1500. Springer, Singapore. https://doi.org/10.1007/978-981-16-8062-5_4
Tran Thanh Dien, Nguyen Thanh-Hai and Nguyen Thai-Nghe. (2021) Deep Matrix Factorization for Learning Resources Recommendation. In: Nguyen N.T., Iliadis L., Maglogiannis I., Trawiński B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science, vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_13 (pdf)
Tran Thanh Dien, Le Duy-Anh, Nguyen Hong-Phat, Nguyen Van-Tuan, Trinh Thanh-Chanh, Le Minh-Bang, Nguyen Thanh-Hai and Nguyen Thai-Nghe (2021). Four Grade Levels-Based Models with Random Forest for Student Performance Prediction at a Multidisciplinary University. In: Barolli L., Yim K., Enokido T. (eds) Complex, Intelligent and Software Intensive Systems. CISIS 2021. Lecture Notes in Networks and Systems, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-030-79725-6_1
Hai Thanh Nguyen, Toan Tran, Nhi Phan Kim Yen, Dien Tran Thanh and Nguyen Thai-Nghe. (2021) Feature Selection Based on Shapley Additive Explanations on Metagenomic Data for Colorectal Cancer Diagnosis. In: Phuong N.H., Kreinovich V. (eds) Soft Computing: Biomedical and Related Applications. Studies in Computational Intelligence, vol 981. Springer, Cham. https://doi.org/10.1007/978-3-030-76620-7_6
Nguyen Thanh-Hai and Nguyen Thai-Nghe. Diagnosis Approaches for Colorectal Cancer using Manifold Learning and Deep Learning. SN Computer Science. 1, 281 (2020). ISSN: 2661-8907. Springer. DOI: https://doi.org/10.1007/s42979-020-00297-7
Tran Thanh Dien, Nguyen Thanh-Hai, Nguyen Thai-Nghe. Deep Learning Approach for Automatic Topic Classification in An Online Submission System. Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 700-709 (2020). ISSN: 2415-6698. DOI: 10.25046/aj050483.
Nguyen Thai-Nghe and Nguyen Thanh-Hai. 2020, Forecasting Sensor Data Using Multivariate Time Series Deep Learning. In: Dang T.K., Küng J., Takizawa M., Chung T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2020. Communications in Computer and Information Science, vol 1306. Springer, Singapore. https://doi.org/10.1007/978-981-33-4370-2_16
Tran Thanh Dien, Sang Hoai Luu, Nguyen Thanh-Hai and Nguyen Thai-Nghe. Deep Learning with Data Transformation and Factor Analysis for Student Performance Prediction. International Journal of Advanced Computer Science and Applications (IJACSA), pp 711-721, 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110886 (pdf)
Tran Thanh Dien, Luu Hoai Sang, Thanh Hai Nguyen, Nguyen Thai-Nghe. 2020. Course Recommendation with Deep Learning Approach. In: Dang T.K., Küng J., Takizawa M., Chung T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2020. Communications in Computer and Information Science, vol 1306. Springer, Singapore. https://doi.org/10.1007/978-981-33-4370-2_5
Nguyen Thanh-Hai, Tran Bao Toan, Cong An Tran and Nguyen Thai-Nghe. 2020. Feature Selection Using Local Interpretable Model-Agnostic Explanations on Metagenomic Data. In: Dang T.K., Küng J., Takizawa M., Chung T.M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2020. Communications in Computer and Information Science, vol 1306. Springer, Singapore. https://doi.org/10.1007/978-981-33-4370-2_24
Huynh-Ly Thanh-Nhan, Le Huy-Thap and Nguyen Thai-Nghe. 2020. Integrating courses' relationship into predicting student performance, International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE), pp. 6375-6383, Vol. 9, No 4, 2020. ISSN: 2278–3091.
Nguyen Thai-Nghe, Nguyen Thanh-Hai and Nguyen Chi Ngon. Deep Learning Approach for Forecasting Water Quality in IoT Systems. International Journal of Advanced Computer Science and Applications (IJACSA), pp. 686-693, 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110883.
Nguyen Thai-Nghe, Tran Thanh Hung, and Nguyen Chi Ngon. 2020. A Forecasting Model for Monitoring Water Quality in Aquaculture and Fisheries IoT Systems. In Proceedings of The International Conference on Advanced COMPuting and Applications (ACOMP 2020). pp 165-169, IEEE. DOI 10.1109/ACOMP50827.2020.00033
Tran Thanh Dien, Le Van Trung and Nguyen Thai-Nghe. An approach for semantic-based searching in learning resources. The 12th IEEE International Conference on Knowledge and Systems Engineering (KSE 2020). pp 183-188, IEEE.
Linh My Thi Ong, Nghe Thai Nguyen, Huong Hoang Luong, Nghi C. Tran, and Hiep Xuan Huynh. 2020. Cyber Physical System: Achievements and challenges. In Proceedings of the 4th International Conference on Machine Learning and Soft Computing (ICMLSC 2020). Association for Computing Machinery, New York, NY, USA, 129–133. DOI:https://doi.org/10.1145/3380688.3380695
Tran Thanh Dien, Huynh Ngoc Han and Nguyen Thai-Nghe. 2019. An Approach for Plagiarism Detection in Learning Resources. In: Dang T., Küng J., Takizawa M., Bui S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science, pp 722-730 , vol 11814. Springer, Cham. DOI https://doi.org/10.1007/978-3-030-35653-8_52.
Thanh Hai Nguyen and Nguyen Thai-Nghe. 2019. Disease Prediction Using Metagenomic Data Visualizations Based on Manifold Learning and Convolutional Neural Network. In: Dang T., Küng J., Takizawa M., Bui S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science, pp 117-131, vol 11814. Springer, Cham. DOI https://doi.org/10.1007/978-3-030-35653-8_9.
Tran Thanh Dien, Bui Huu Loc and Nguyen Thai-Nghe. 2019. Article Classification using Natural Language Processing and Machine Learning. In Proceedings of the 2019 International Conference on Advanced Computing and Applications (ACOMP), pp. 78-84. ISBN: 978-1-7281-4723-9. DOI: 10.1109/ACOMP.2019.00019. IEEE. (pdf)
Nguyen Hong Son and Nguyen Thai-Nghe, 2019. Deep Learning for Rice Quality Classification. In Proceedings of the 2019 International Conference on Advanced Computing and Applications (ACOMP), pp. 92-96, ISBN: 978-1-7281-4723-9. DOI: 10.1109/ACOMP.2019.00021. IEEE. (pdf)
Huynh Thanh-Tai and Nguyen Thai-Nghe. 2017. A Semantic-Based Recommendation Approach for Cold-Start Problem. In: Dang T., Wagner R., Küng J., Thoai N., Takizawa M., Neuhold E. (eds) Future Data and Security Engineering. FDSE 2017. Lecture Notes in Computer Science, vol 10646. Springer, Cham. DOI https://doi.org/10.1007/978-3-319-70004-5_31.
Nguyen Thai-Nghe, Mai Nhut-Tu, and Huu-Hoa Nguyen. 2017. An Approach for Multi-Relational Data Context in Recommender Systems. In: Nguyen N., Tojo S., Nguyen L., Trawiński B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science, pp. 709-720, vol 10191. Springer, Cham. DOI: https://doi.org/10.1007/978-3-319-54472-4_66 (pdf)
Huynh-Ly Thanh-Nhan, Le Huy-Thap and Nguyen Thai-Nghe. 2017. Toward integrating social networks into intelligent tutoring systems, 2017 9th International Conference on Knowledge and Systems Engineering (KSE 2017), pp. 112-117. DOI: 10.1109/KSE.2017.8119444. IEEE.
Huynh Thanh-Tai, Huu-Hoa Nguyen, and Nguyen Thai-Nghe. 2016. A Semantic Approach in Recommender Systems. In: Dang T., Wagner R., Küng J., Thoai N., Takizawa M., Neuhold E. (eds) Future Data and Security Engineering. FDSE 2016. Lecture Notes in Computer Science, pp 331-343, vol 10018. Springer, Cham. DOI 10.1007/978-3-319-48057-2_23.
Luu Nguyen Anh-Thu, Huu-Hoa Nguyen and Nguyen Thai-Nghe. 2016. A Context-Aware Implicit Feedback Approach for Online Shopping Recommender Systems. In: Nguyen N.T., Trawiński B., Fujita H., Hong TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science, pp 584-593, vol 9622. Springer, Berlin, Heidelberg. DOI 10.1007/978-3-662-49390-8_57.
Huynh Ly Thanh-Nhan, Huu-Hoa Nguyen, and Nguyen Thai-Nghe. 2016. Methods for building course recommendation systems. In Proceedings of the 2016 International Conference on Knowledge and Systems Engineering (KSE 2016), pp.163-168, ISBN 978-1-4673-8929-7, IEEE.
Nguyen Thanh-Hai, Huu-Hoa Nguyen and Nguyen Thai-Nghe. 2016. A Mobility Prediction Model for Location-Based Social Networks. In: Nguyen N.T., Trawiński B., Fujita H., Hong TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science, pp 106-115, vol 9621. Springer, Berlin, Heidelberg. DOI 10.1007/978-3-662-49381-6_11.
Nguyen Thai-Nghe, Lars Schmidt-Thieme. 2015. Factorization Forecasting Approach for User Modeling. Journal of Computer Science and Cybernetics. 133-148. Vol 31, No 2. ISSN: 1813-9663. DOI: 10.15625/1813-9663/31/2/5860
Nguyen Thai-Nghe and Quoc Dinh Truong. 2015. An Approach for Building A Semi-Automatic Online Consultancy System. Proceedings of International Conference on Advanced Computing and Applications (ACOMP 2015). pp 51-58, ISBN-13: 978-1-4673-8234-2, IEEE.
Nguyen Chi-Ngon and Nguyen Thai-Nghe. 2015. An Agricultural Extension Support System on Mobile Communication Networks. Proceedings of International Conference on Advanced Technologies for Communications (ATC 2015). pp. 534-539. ISBN 978-1-4673-8372-1. IEEE.
Nguyen Thai-Nghe and Lars Schmidt-Thieme. 2015. Multi-Relational Factorization Models for Student Modeling in Intelligent Tutoring Systems. In proceedings of the 2015 Seventh International Conference on Knowledge and Systems Engineering (KSE 2015). pp. 61-66, ISBN 978-1-4673-8013-3, IEEE.
Tran Nguyen Minh-Thai and Nguyen Thai-Nghe. 2015. Methods for Abnormal Usage Detection in Developing Intelligent Systems for Smart Homes. In proceedings of the 2015 Seventh International Conference on Knowledge and Systems Engineering (KSE 2015). pp. 114-119, ISBN 978-1-4673-8013-3, IEEE.
Tran Nguyen Minh-Thai and Nguyen Thai-Nghe. 2015. An Approach for Developing Intelligent Systems in Smart Home Environment. In: Dang T., Wagner R., Küng J., Thoai N., Takizawa M., Neuhold E. (eds) Future Data and Security Engineering. FDSE 2015. Lecture Notes in Computer Science, pp 147-161, vol 9446. Springer, Cham.
Bich-Thuy Dong Thi, Alexis Drogoul, Pierre Kuonen, Cao-De Tran, An Cong Tran, and Nguyen Thai-Nghe. 2015. Proceedings of the 2015 IEEE RIVF International Conference on Computing & Communication Technologies - Research, Innovation, and Vision for the Future (RIVF). IEEE Xplore. ISBN (Print): 978-1-4799-8043-7
Nguyen Thai-Nghe and Nguyen Chi-Ngon. 2014. An Approach for Building an Intelligent Parking Support System. In Proceedings of the Fifth Symposium on Information and Communication Technology (SoICT '14). ACM, New York, NY, USA. pp. 192-201. ISBN: 978-1-4503-2930-9. (pdf)
Nguyen Thai-Nghe. 2013. An introduction to factorization technique for building recommendation systems. Vol. 6/2013, pp. 44-53, Journal of Science - University of Da Lat, ISSN 0866-787X.
Nguyen Thai-Nghe, Zeno Gantner, and Lars Schmidt-Thieme. 2013. An Evaluation Measure for Learning from Imbalanced Data Based on Asymmetric Beta Distribution. Book Chapter in Classification and Data Mining: Studies in Classification, Data Analysis, and Knowledge Organization, pp. 121-129. Print ISBN: 978-3-642-28893-7. Series ISSN: 1431-8814. Springer.
Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, Artus Krohn-Grimberghe, Alexandros Nanopoulos, and Lars Schmidt-Thieme. 2012. Factorization Techniques for Predicting Student Performance. Book chapter in Educational Recommender Systems and Technologies: Practices and Challenges (ERSAT 2012). Santos, O. C. and Boticario, J. G. (Eds.). pp. 129-153. ISBN13: 9781613504895, IGI Global Publisher. Scopus. (java source codes)
Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, and Lars Schmidt-Thieme. 2012. Using Factorization Machines for Student Modeling. Proceedings of FactMod 2012 at the 20th Conference on User Modeling, Adaptation, and Personalization (UMAP 2012). Vol. 872, CEUR-WS, ISSN: 1613-0073. Scopus.
Lucas Drumond , Nguyen Thai-Nghe, Tomáš Horváth, and Lars Schmidt-Thieme. 2012. Factorization techniques for student performance classification and ranking, in proceedings of FactMod 2012 WS at the 20th Conference on User Modeling, Adaptation, and Personalization (UMAP 2012). Vol. 872, CEUR-WS, ISSN: 1613-0073. Scopus.
Van Toan Vo, Thanh Binh Nguyen, and Nguyen Thai-Nghe. 2012. Efficient Hybrid Cascading Numerical Character Classification for Automatic Meter Reading System, in proceedings of The 8th International Conference on Multimedia Information Technology and Applications (MITA 2012)
Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, and Lars Schmidt-Thieme. 2011. Multi-Relational Factorization Models for Predicting Student Performance, in proceedings of the 17th ACM SIGKDD 2011 Workshop on Knowledge Discovery in Educational Data (KDDinED 2011).
Nguyen Thai-Nghe, Tomáš Horváth, and Lars Schmidt-Thieme. 2011. Factorization Models for Forecasting Student Performance, in Pechenizkiy, M., Calders, T., Conati, C., Ventura, S., Romero , C., and Stamper, J. (Eds.) Proceedings of the 4th International Conference on Educational Data Mining (EDM 2011). ISBN 978-90-386-2537-9. Scopus.
Nguyen Thai-Nghe, Tomáš Horváth, and Lars Schmidt-Thieme. 2011. Context-Aware Factorization for Personalized Student's Task Recommendation, in Proceedings of UMAP 2011 International Workshop on Personalization Approaches in Learning Environments (PALE), CEUR, ISSN 1613-0073. Scopus.
Nguyen Thai-Nghe, Zeno Gantner, and Lars Schmidt-Thieme. 2011. A New Evaluation Measure for Learning from Imbalanced Data, in proceedings of IEEE International Joint Conference on Neural Networks (IJCNN 2011),pp. 537 - 542. ISSN 2161-4393. Print ISBN 978-1-4244-9635 8. IEEE Xplore. Student Travel Grant Award
Nguyen Thai-Nghe, Tomáš Horváth, and Lars Schmidt-Thieme. 2011. Personalized Forecasting Student Performance, in Proceedings of the 11th IEEE International Conference on Advanced Learning Technologies (ICALT 2011). pp. 412 - 414. ISBN: 978-1-61284-209-7. IEEE Xplore. Scopus.
Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, Alexandros Nanopoulos, and Lars Schmidt-Thieme. 2011. Matrix and Tensor Factorization for Predicting Student Performance, in Proceedings of the 3rd International Conference on Computer Supported Education (CSEDU 2011). pp. 69-78. SciTePress 2011. ISBN: 978-989-8425-49-2. Best student paper award
Nguyen Thai-Nghe, Lucas Drumond, Artus Krohn-Grimberghe, and Lars Schmidt-Thieme. 2010. Recommender System for Predicting Student Performance. Volume 1, Issue 2, 2010, Pages 2811-2819, Elsevier Computer Science Procedia. ISSN: 1877-0509. Scopus.
Nguyen Thai-Nghe, Thanh-Nghi Do, and Lars Schmidt-Thieme. 2010. Learning Optimal Threshold for Bayesian Posterior Probabilities to Mitigate Class Imbalance Problem, vol. 48, No. 4, pp.38-49, JOURNAL OF SCIENCE AND TECHNOLOGY, ISSN: 0866-708x.
Nguyen Thai-Nghe, Thanh-Nghi Do, and Lars Schmidt-Thieme. 2010. Learning Optimal Threshold on Resampling Data to Deal with Class Imbalance, in proceedings of IEEE RIVF 2010 International Conference on Computing and Telecommunication Technologies (RIVF 2010), pp. 71-76. ISBN: 978-1-4244-8072-2. IEEE.
Nguyen Thai-Nghe, Zeno Gantner, and Lars Schmidt-Thieme. 2010. Cost-Sensitive Learning Methods for Imbalanced Data, in proceedings of IEEE International Joint Conference on Neural Networks (IJCNN 2010), ISBN: 978-1-4244-6916-1. IEEE. Student Travel Grant Award
Nguyen Thai-Nghe, Andre Busche, and Lars Schmidt-Thieme. 2009. Improving Academic Performance Prediction by Dealing with Class Imbalance, in Proceedings of the 9th IEEE International Conference on Intelligent Systems Design and Applications (ISDA 2009), pp. 878-883. ISBN: 978-0-7695-3872-3. IEEE Computer Society. Washington, DC, USA ©2009.
Nguyen Thai-Nghe, Paul Janecek, and Peter Haddawy. 2007. A comparative analysis of techniques for predicting academic performance, in Proceedings of the 37th ASEE/IEEE Frontiers in Education (FIE 2007), pp. T2G-7-T2G-12. ISSN: 0190-5848. E-ISBN: 978-1-4244-1084-2. Print ISBN: 978-1-4244-1083-5. IEEE.
Chi-Ngon Nguyen, Thanh-Hung Tran, Thanh-Tuyen T. Truong, and Nguyen Thai-Nghe. 2005. A method of control system by Vietnamese speech using Neural Networks, in Proceedings of the 3rd RIVF - International Conference on Research, Innovation and Vision for the Future in ICT (RIVF 2005), pp. 315-317.