Zengvan Zhang

Title: Zengvan Zhang: Innovator in Adaptive Targeting Technology

Introduction

Zengvan Zhang is a notable inventor based in San Jose, CA. He has made significant contributions to the field of internet advertising through his innovative patent. His work focuses on adaptive targeting methods that enhance the effectiveness of online advertisements.

Latest Patents

Zengvan Zhang holds a patent for "Adaptive targeting for finding look-alike users." This method involves the adaptive display of internet advertisements to look-alike users by utilizing a desired user profile dataset as a seed for machine learning modules. The process begins with mapping the desired user profile to other look-alike users from a larger database. It normalizes both the desired and known user profile objects, subsequently seeding a machine-learning training model with the normalized data. A scoring engine then matches users based on extracted features. Once look-alike users are identified, the internet display system serves advertisements to them and analyzes their behaviors, allowing for the adaptation of the user profile dataset to changing user behavior.

Career Highlights

Zengvan Zhang is currently employed at Yahoo! Inc., where he applies his expertise in machine learning and user profiling. His innovative approach to adaptive targeting has positioned him as a key player in the evolution of online advertising strategies.

Collaborations

Zengvan collaborates with talented individuals such as Andrew Hatch and Abraham Hossain Bagherjeiran. Their combined efforts contribute to the advancement of technology in the advertising sector.

Conclusion

Zengvan Zhang's work in adaptive targeting represents a significant advancement in the field of internet advertising. His innovative methods not only enhance user experience but also improve the effectiveness of advertising strategies.