Jerusalem, Israel

Yehezkal Shraga Resheff


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2021-2022

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2 patents (USPTO):Explore Patents

Title: Yehezkal Shraga Resheff: Innovator in Machine Learning and Data Scraping

Introduction

Yehezkal Shraga Resheff is a notable inventor based in Jerusalem, Israel. He has made significant contributions to the fields of machine learning and data scraping, holding a total of 2 patents. His work focuses on enhancing recommendation systems and automating data extraction processes.

Latest Patents

Resheff's latest patents include innovative methods that leverage machine learning techniques. One of his patents, titled "Adversarial user representations in recommender machine learning models," outlines a method for generating recommendations and user structures. This method applies a recommender machine learning model to training user information and item information. It also generates demographic predictions of users, which are used to improve the accuracy of recommendations. Another patent, "Automated data scraping," describes a method for extracting identifier-value pairs from documents. This method involves determining the correct definitions of positions within the text to facilitate efficient data scraping.

Career Highlights

Yehezkal Shraga Resheff is currently employed at Intuit, Inc., where he continues to develop innovative solutions in technology. His expertise in machine learning and data processing has positioned him as a valuable asset in his field.

Collaborations

Throughout his career, Resheff has collaborated with talented individuals such as Shimon Shahar and Oren Sar Shalom. These collaborations have contributed to the advancement of his projects and innovations.

Conclusion

Yehezkal Shraga Resheff is a prominent inventor whose work in machine learning and data scraping has led to significant advancements in technology. His contributions continue to influence the way data is processed and recommendations are generated.

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