Norwalk, CT, United States of America

Michael Van Patten


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Michael Van Patten: Innovator in Data Personalization Technology

Introduction

Michael Van Patten is an accomplished inventor based in Norwalk, CT (US). He has made significant contributions to the field of data personalization through his innovative patent. His work focuses on enhancing the way entities are rated and selected based on user preferences and machine learning techniques.

Latest Patents

Van Patten holds a patent for a "Counting machine for data and confidential personalization of proprietary entity ratings via Minkowski-distance semi-supervised machine learning." This invention comprises an electronic device equipped with a display, user interface, and memory storage. The device stores a table listing predetermined attribute preferences associated with index numbers computed from user rankings. It allows users to display and partially rank influencing factors, select top and least important factors from adaptive menus, and retrieve predetermined entity rankings derived from expert opinions and machine learning.

Career Highlights

Michael Van Patten has made a notable impact in his field through his innovative approach to data personalization. His patent reflects a deep understanding of user preferences and the application of advanced machine learning techniques. He is currently associated with Esg-rate, Inc., where he continues to develop and refine his ideas.

Collaborations

Van Patten has worked alongside talented individuals such as Lawrence C Rafsky and Thomas J Saleh. Their collaboration has likely contributed to the advancement of their shared goals in the realm of data technology.

Conclusion

Michael Van Patten is a pioneering inventor whose work in data personalization technology is shaping the future of entity ratings. His innovative patent demonstrates his commitment to enhancing user experience through advanced machine learning applications.

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