Company Filing History:
Years Active: 2024
Title: **Shih Bo Lin: Innovator in Live Streaming Data Categorization**
Introduction
Shih Bo Lin, an inventive mind based in Tokyo, Japan, has made notable contributions to the field of live streaming technology. With a keen focus on enhancing user experience through data categorization, he has secured a patent that showcases his innovative approach in this rapidly evolving domain.
Latest Patents
Shih Bo Lin holds a significant patent titled "System, method and computer-readable medium for categorizing live streaming data." This invention relates to an advanced methodology for tagging live streaming programs. Specifically, the method includes generating a first intermediate tag and a second intermediate tag, ultimately leading to a final tag based on the initial intermediates. This innovative approach allows for a more granular and precise categorization of content, improving how users can navigate and discover live streaming material.
Career Highlights
Shih Bo Lin is currently affiliated with 17Live Japan Inc., a company dedicated to enhancing live streaming interactions. His work at the company emphasizes the importance of effective data handling to provide exceptional user experiences. Through his patent, Shih demonstrates his commitment to innovation and technological advancement in the live streaming sector.
Collaborations
In his professional journey, Shih Bo Lin collaborates with fellow innovators Hemanth Kumar Ajaru and Kshitiz Yadav. Together, they contribute to exciting projects, pushing the boundaries of what is possible in live streaming technologies and data categorization.
Conclusion
Shih Bo Lin stands out as a prominent inventor in the tech landscape, particularly for his work on improving live streaming data categorization. His dedication to innovation not only enhances the capabilities of platforms like 17Live Japan Inc. but also sets a benchmark for future developments in the industry. As technology continues to evolve, Shih Bo Lin's contributions will undoubtedly have a lasting impact on the way live streaming data is managed and categorized.