Jun Xu

Title: Jun Xu: Innovator in Cloud-Native Technologies

Introduction

Jun Xu is a prominent inventor based in Zhejiang, China. He has made significant contributions to the field of cloud-native technologies, particularly in application programming interfaces (APIs). With a total of 2 patents, his work focuses on enhancing service recommendation models through innovative methods.

Latest Patents

One of Jun Xu's latest patents is a cloud-native application programming interface (API) recommendation method that fuses data augmentation and contrastive learning. This method includes service information based on a service information double-graph structure. A mutual attention mechanism is designed to compute the importance degree of each layer of information. Additionally, it provides a data optimization method for sequence information based on functional similarity and a computation method for similarity between services based on two parts of information. The data of a service invocation sequence is augmented using contrastive learning to form an augmented sequence pair. A computational contrastive loss function is combined with a pair-wise recommendation loss function to optimize the overall model, thereby improving the effectiveness of the service recommendation model. Ultimately, pair-wise recommendation scores are computed based on a feature embedding representation result of a service to complete the service recommendation process.

Career Highlights

Throughout his career, Jun Xu has worked with notable organizations, including Lanxi Yide Textile Co., Ltd and China Jiliang University. His experience in these companies has contributed to his expertise in the field of technology and innovation.

Collaborations

Jun Xu has collaborated with various professionals, including Jiawei Lu, to further enhance his research and development efforts.

Conclusion

Jun Xu is a dedicated inventor whose work in cloud-native technologies and API recommendations showcases his innovative spirit. His contributions are paving the way for advancements in service recommendation models, making a significant impact in the tech industry.