Nguyen Thi Kim Anh

Associate Professor, Department Of Computer Science

Ph.D. (Computer Science, HaNoi University of Science and Technology, 1994)
B.S. (Computer Science, HaNoi University of Science and Technology)

Email: anhnk@soict.hust.edu.vn
Web:  

• Data Analytics
• Knowledge Discovery from Big Databases and Social Network
• Text mining and Web mining 

• Data Warehouse and OLAP
• Deep Learning
• Graphical Model
• Knowledge Discovery from Big Databases and Social Network
• Text mining and Web mining 

Nguyen Thi Kim Anh is a Associate Professor of Computer Science at the School of Information and Communication Technology, HaNoi University of Science and Technology (HUST). She received her Ph.D. in computer science in 1994 from HUST. Her current research interests include advanced database systems, data warehouse and OLAP, data analytics, deep learning, Knowledge Discovery from Big Databases and Social Network, Text mining and Web mining.

• Thanh Ha Thi, Chinh Nguyen Thanh, Kiem-Hieu Nguyen, Chung Vu Van and Anh Nguyen Kim.Unsupervised Sentence Embeddings for Answer Summarization in Non-factoid CQA.CICLING 2018.
• Ngo Van Linh, Nguyen Kim Anh, Khoat Than, Chien Nguyen Dang, “An Effective and Interpretable Method for Document Classification”, Knowledge and Information Systems (KAIS), Volume 50, Issue 3, pp 763–793, 2017.
• Duc-Anh Nguyen, Kim Anh Nguyen, Linh Ngo, Khoat Than, “Keeping priors in streaming Bayesian learning”, Advances in Knowledge Discovery and Data Mining. PAKDD 2017.Lecture Notes in Computer Science, vol 10234. Springer, 2017.
• Khai Mai, Sang Mai, Anh Nguyen, Linh Ngo, Khoat Than, “Enabling Hierarchical Dirichlet Processes to work better for short texts at large scale”, In Proceedings of PAKDD. Lecture Notes in Computer Science, Springer, 2016.
• Khai Mai, Sang Mai, Anh Nguyen, Ngo Van Linh, Khoat Than, “Bag-of-biterms representation for short texts”, In submission to JMLC,
• Ngo Van Linh, Nguyen Kim Anh, Khoat Than, Chien Nguyen Dang, “An Effective and Interpretable Method for Document Classification”, Knowledge and Information Systems, 2016. (ISI)
• Mai Tien Khai, Mai Anh Sang, Nguyen Kim Anh, Ngo Van Linh, Khoat Than, “Enabling Hierarchical Dirichlet Processes to work better for short texts at large scale”, In Proceedings of PAKDD, Lecture Notes in Computer Science, Springer, vol. 9652, pages 431-442, 2016.
• Ngo Van Linh, Nguyen Kim Anh, Khoat Than, Nguyen Tat Nguyen, “Effective and Interpretable Document Classification using Distinctly Labeled Dirichlet Process Mixture Models of von Mises-Fisher Distributions”, In Proceedings of DASFAA. Lecture Notes in Computer Science, Springer, vol. 9050, pages 139-153, 2015.
• Linh Ngo Van, Anh Nguyen Kim, and Khoat Than, “An effective NMF-based method for supervised dimension reduction”. In Proceedings of the KSE, 2014.
• Nguyen Kim Anh, Nguyen The Tam and Ngo Van Linh, Document Clustering using Mixture Model of von Mises-Fisher Distributions on Document Manifold, 2013 International Conference of Soft Computing and Pattern Recognition (SoCPaR), pp.146-151.
• Nguyen Kim Anh, Ngo Van Linh, Nguyen Khac Toi, Nguyen The Tam , Multi-labeled Document Classification using Semi-supervived Mixture Model of Watson distributions on Document Manifold, 2013 International Conference of Soft Computing and Pattern Recognition (SoCPaR), pp.129-134.
• Nguyen Kim Anh, Nguyen The Tam and Ngo Van Linh, Document Clustering using Dirichlet Process Mixture Model of von Mises-Fisher Distributions, In Proceedings of the 4^th Symposium on Information and Communication Technology (SoICT 2013), pp.131-138.
• Nguyen Kim Anh, Ngo Van Linh, Lê Hồng Kỳ and Nguyen The Tam, Document Classification using Semi-supervived Mixture Model of von Mises-Fisher Distributions on Document Manifold, In Proceedings of the 4^th Symposium on Information and Communication Technology (SoICT 2013), pp.94-100.

• A government project 2011-2013: Principle Investigator
• Flemish Interuniversity Council for University Development Cooperation(2006-2008): Member
• Nafosted 2014-2016: Member
• AFOSR (6/2015—5/2017): Member

• IT3090: Database Systems
• IT4310: Advanced Databases
• IT4753: Introduction to Machine Learning
• IT5429: Graph Analytics with Big Data
• IT6060: Advanced Database Systems