New York, NY, United States of America

Karl Moritz Hermann


Average Co-Inventor Count = 4.0

ph-index = 2

Forward Citations = 19(Granted Patents)


Company Filing History:


Years Active: 2016-2019

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2 patents (USPTO):Explore Patents

Title: Karl Moritz Hermann: Innovator in Semantic Frame Identification

Introduction

Karl Moritz Hermann is a notable inventor based in New York, NY (US). He has made significant contributions to the field of computer science, particularly in the area of semantic frame identification. With a total of 2 patents, Hermann's work has advanced the understanding of word representations in computational linguistics.

Latest Patents

One of his latest patents is focused on semantic frame identification with distributed word representations. This computer-implemented technique involves receiving labeled training data that includes various groups of words, each associated with a predicate word. The process includes extracting these groups in the syntactic context of their predicate words and concatenating generic word embeddings to create a high-dimensional vector space. Furthermore, the technique obtains a model that maps this high-dimensional space to a low-dimensional one, allowing for the identification of specific semantic frames for inputs.

Career Highlights

Karl Moritz Hermann is currently employed at Google Inc., where he continues to innovate and develop new techniques in the realm of artificial intelligence and natural language processing. His work has been instrumental in enhancing the capabilities of machine learning models in understanding human language.

Collaborations

Hermann has collaborated with notable colleagues such as Dipanjan Das and Kuzman Ganchev, contributing to various projects that push the boundaries of technology and innovation.

Conclusion

Karl Moritz Hermann's contributions to semantic frame identification and his work at Google Inc. highlight his role as a leading inventor in the field of computer science. His innovative techniques continue to shape the future of natural language processing.

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