Mountain View, CA, United States of America

Tzu-Ting Kuo


Average Co-Inventor Count = 2.3

ph-index = 2

Forward Citations = 8(Granted Patents)


Location History:

  • Palo Alto, CA (US) (2020)
  • Mountain View, CA (US) (2021 - 2023)

Company Filing History:


Years Active: 2020-2024

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5 patents (USPTO):Explore Patents

Title: Innovations of Tzu-Ting Kuo

Introduction

Tzu-Ting Kuo is a notable inventor based in Mountain View, California. He has made significant contributions to the field of sentiment analysis, holding a total of five patents. His work focuses on developing systems and methods that enhance the understanding of sentiment in text strings.

Latest Patents

Among his latest patents is a system and method for identifying sentiment in text strings. This invention refers to systems and methods for identifying relevantly similar sentiment in text strings. Another significant patent is a system and method for detecting the portability of sentiment analysis systems based on changes in a sentiment confidence score distribution. This invention provides a system that determines whether a sentiment analysis model is portable between two data sets. The system analyzes the text of reviews using the sentiment analysis model to determine the sentiment expressed. It computes a confidence score indicating the accuracy of the sentiment and assesses the significance of changes between confidence score distributions.

Career Highlights

Tzu-Ting Kuo is currently employed at Medallia, Inc., where he applies his expertise in sentiment analysis. His innovative work has contributed to advancements in understanding consumer sentiment through data analysis.

Collaborations

He collaborates with talented coworkers, including Ji Fang and Gregor Stewart, who contribute to the innovative environment at Medallia, Inc.

Conclusion

Tzu-Ting Kuo's contributions to sentiment analysis through his patents and work at Medallia, Inc. highlight his role as a significant inventor in the field. His innovative systems and methods continue to advance the understanding of sentiment in text analysis.

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