Minyue Zhang

Title: Minyue Zhang: Innovator in Patent Classification and Evaluation

Introduction

Minyue Zhang is a prominent inventor based in Beijing, China. He has made significant contributions to the field of patent classification and evaluation, holding 2 patents that showcase his innovative approach to these complex processes.

Latest Patents

One of his latest patents is an "Automatic Industry Classification Method and System." This invention involves determining a scope of target patents and defining a target industry tree. It generates marks on the target industry tree and performs both rough and fine classifications for the target patents. The method utilizes a transductive learning approach, allowing for the effective mining of small annotation quantity information. Additionally, it enriches information dimensions by using IPC data, thereby reducing the computational load required for classification. Another notable patent is the "Patent Evaluation Method and System that Aggregate Patents Based on Technical Clustering." This method collects patent documents and generates technical points and clusters for evaluation. It employs natural language processing and complex network algorithms to aggregate patents within technical clusters, providing scientific and technological attributes for a comprehensive evaluation.

Career Highlights

Minyue Zhang has worked with several notable companies, including Beijing Benying Technologies Co., Ltd. and Beijing Innovator Information Technology Co., Ltd. His work in these organizations has furthered his expertise in patent-related technologies and methodologies.

Collaborations

Throughout his career, Minyue has collaborated with talented individuals such as Kai Cao and Weining Li, who have contributed to his projects and innovations.

Conclusion

Minyue Zhang's contributions to patent classification and evaluation demonstrate his innovative spirit and commitment to advancing technology in this field. His patents reflect a deep understanding of the complexities involved in patent analysis and classification.