San Jose, CA, United States of America

Jianpeng Xu


Average Co-Inventor Count = 5.2

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2022-2025

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5 patents (USPTO):Explore Patents

Title: Innovations by Jianpeng Xu

Introduction

Jianpeng Xu is a notable inventor based in San Jose, California. He has made significant contributions to the field of technology, particularly in recommendation systems. With a total of five patents to his name, Xu's work focuses on enhancing user experience through advanced algorithms and machine learning techniques.

Latest Patents

One of Jianpeng Xu's latest patents is titled "Systems and methods for recommendation system analysis." This invention involves a system that utilizes processors and non-transitory computer-readable media to analyze user requests for product searches. The system determines the processing mode and identifies candidate recommendation systems to optimize product recommendations based on user queries.

Another significant patent is "Similar item recommendation framework using wide-and-deep-architecture." This system employs machine learning to predict similar items by combining outputs from different models. It generates a similarity score for items and displays recommendations on a website, enhancing the shopping experience for users.

Career Highlights

Jianpeng Xu currently works at Walmart Apollo, LLC, where he applies his expertise in developing innovative solutions for product recommendations. His work has been instrumental in improving the efficiency and effectiveness of recommendation systems, which are crucial for online retail.

Collaborations

Throughout his career, Xu has collaborated with talented professionals, including Sriram Guna Sekhar Kollipara and Kannan Achan. These collaborations have contributed to the advancement of technology in the field of recommendation systems.

Conclusion

Jianpeng Xu's contributions to the field of technology through his innovative patents and collaborative efforts have significantly impacted the way users interact with online platforms. His work continues to shape the future of recommendation systems, making online shopping more intuitive and user-friendly.

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