Hung-Li Chen

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Differential privacy is a recent notion of data privacy protection, which does not matter even when an attacker has arbitrary background knowledge in advance. Consequently, it is viewed as a reliable protection mechanism for sensitive information. Differential privacy introduces Laplace noise to hide the true value in a dataset while preserving statistic(More)
Personal time logs are collected by many people to provide insights of their work patterns and life patterns. However, the visualizations provided by the time tracking tools do not provide easy exploration and analysis. Schedulvis is designed and implemented to help people analyze personal time log data on desired long term activities. The system contains(More)
As more and more technologies to store and analyze massive amount of data become available, it is extremely important to make privacy-sensitive data de-identified so that further analysis can be conducted by different parties. For example, data needs to go through data de-identification process before being transferred to institutes for further value added(More)
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