@misc{17345,
  author = {Phuc Nguyen and Linh Tran and Bao Le and Thuong Nguyen and Thu Nguyen and Hien Nguyen and Binh Nguyen},
  title = {Faster Imputation Using Singular Value Decomposition for Sparse Data},
  abstract = {With the emergence of many knowledge-based systems worldwide, there have been more and more applications using different kinds of data and solving significant daily problems. Among that, the issues of missing data in such systems have become more popular, especially in data-driven areas. Other research on the imputation problem has dealt with partial and missing data. This study aims to investigate the imputation techniques for sparse data using the Singular Value Decomposition technique, namely SVDI. We explore the application of the SVDI framework for image classification and text classification tasks that involve sparse data. The experimental results show that the proposed SVDI method improves the speed and accuracy of the imputation process when compared to the PCAI method. We aim to publish our codes related to the SVDI later for the relevant research community.},
  year = {2023},
  journal = {Asian Conference on Intelligent Information and Database Systems},
  volume = {Lecture Notes in Computer Science, vol 13995},
  pages = {135-146},
  publisher = {Springer},
  url = {https://link.springer.com/chapter/10.1007/978-981-99-5834-4_11},
}