Mountain View, CA, United States of America

Jinfeng Li


Average Co-Inventor Count = 9.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023-2024

where 'Filed Patents' based on already Granted Patents

2 patents (USPTO):

Title: Innovations of Jinfeng Li

Introduction

Jinfeng Li is an accomplished inventor based in Mountain View, CA (US). He has made significant contributions to the field of natural language processing, holding a total of 2 patents. His work focuses on enhancing review comprehension through advanced techniques that leverage domain-specific knowledgebases.

Latest Patents

Jinfeng Li's latest patents include systems and methods for enhanced review comprehension using domain-specific knowledgebases. The disclosed embodiments relate to natural language processing. Techniques can include receiving input text, extracting, from the input text, at least one modifier and aspect pair, receiving data from a knowledgebase based on the at least one modifier and aspect pair and commonsense data, generating one or more premise embeddings, converting the input text into tokens, generating at least one vector for one or more of the tokens based on an analysis of the tokens, combining the at least one vector with the one or more premise embeddings to create at least one combined vector, and analyzing the at least one combined vector wherein the analysis generates an output indicative of a feature of the input text.

Career Highlights

Jinfeng Li is currently employed at Recruit Co., Ltd., where he continues to innovate and develop new technologies. His expertise in natural language processing has positioned him as a key player in his field.

Collaborations

Some of Jinfeng Li's notable coworkers include Yoshihiko Suhara and Behzad Golshan, who contribute to the collaborative environment that fosters innovation.

Conclusion

Jinfeng Li's work in natural language processing and his patents demonstrate his commitment to advancing technology in meaningful ways. His contributions are paving the way for enhanced comprehension systems that can significantly impact various applications.

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