Ding-Jun Yin

Title: The Innovative Contributions of Ding-Jun Yin

Introduction

Ding-Jun Yin is a notable inventor based in Tainan, Taiwan. He has made significant contributions to the field of risk evaluation and data anonymization. With a total of 2 patents, his work focuses on enhancing the efficiency and effectiveness of data handling in various applications.

Latest Patents

Ding-Jun Yin's latest patents include a method and device for risk evaluation. This innovative approach provides a systematic way to evaluate an anonymous dataset generated from an original dataset. The method involves acquiring the frequency of original values, generating a partition set and weight table, and dividing the original dataset into multiple data partitions. By comparing sample data with anonymous data, the method calculates and outputs a risk evaluation result based on matching quantities.

Another significant patent is the generation method and device for creating an anonymous dataset. This method involves acquiring a critical attribute set and a quasi-identifier set, setting an anchor attribute, and generating an equivalence table. The process culminates in the creation of an anonymous dataset that enhances the risk evaluation efficiency by calculating data weight and extracting distinctive data.

Career Highlights

Ding-Jun Yin is affiliated with the Industrial Technology Research Institute, where he applies his expertise in data evaluation and anonymization. His work has been instrumental in advancing methodologies that address data privacy and security concerns.

Collaborations

Ding-Jun has collaborated with notable colleagues, including Ya-Ling Chen and Kuo-Yang Hung. Their combined efforts contribute to the innovative research and development in their field.

Conclusion

Ding-Jun Yin's contributions to the field of risk evaluation and data anonymization are noteworthy. His innovative patents reflect a commitment to improving data handling practices, which is essential in today's data-driven world.