Uppsala, Sweden

Joakim Nivre


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 16(Granted Patents)


Company Filing History:


Years Active: 2016

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1 patent (USPTO):Explore Patents

Title: Joakim Nivre: Innovator in Part-of-Speech Tagging

Introduction

Joakim Nivre, located in Uppsala, Sweden, is an accomplished inventor recognized for his contributions in the field of natural language processing. He has developed a significant innovation that addresses challenges in part-of-speech tagging, particularly benefiting resource-poor languages.

Latest Patents

Nivre holds a patent titled "Weakly supervised part-of-speech tagging with coupled token and type constraints." This patent presents a method and system for a part-of-speech tagger that utilizes manually constructed tag dictionaries derived from dictionaries via bitext, acting as type constraints. This approach aims to tackle the issue of limited annotated data by incorporating additional token constraints projected from a resource-rich source language. The disclosed method demonstrates a significant relative error reduction compared to prior state-of-the-art techniques, showcasing multiple example models, including a partially observed conditional random field model.

Career Highlights

Joakim Nivre currently works at Google Inc., where he applies his expertise to enhance language processing technologies. His innovative spirit and dedication to addressing complex linguistic challenges have positioned him as a forward-thinking leader in the domain.

Collaborations

Throughout his career, Nivre has collaborated with esteemed colleagues, including Slav Petrov and Dipanjan Das. These partnerships highlight the collaborative nature of his work and the importance of teamwork in driving advancements in the field.

Conclusion

Joakim Nivre's contributions to part-of-speech tagging exemplify the power of innovative thinking in addressing linguistic challenges. With his patent and ongoing work at Google Inc., Nivre continues to pave the way for advancements that benefit both resource-poor and resource-rich languages, inspiring emerging inventors and researchers in the field of natural language processing.

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