Wanying Ding

Title: Wanying Ding: Innovator in User Intent Mining and Video Prediction

Introduction

Wanying Ding is a notable inventor based in San Jose, CA, who has made significant contributions to the fields of user intent mining and video prediction. With a total of 3 patents, Ding's work focuses on enhancing the understanding of user behavior and improving video content effectiveness.

Latest Patents

Ding's latest patents include innovative methods that leverage advanced machine learning techniques. One of his patents, titled "Scalable user intent mining using a multimodal restricted boltzmann machine," presents a method for detecting named entities from query logs and generating features based on these entities. This method utilizes a multimodal restricted boltzmann machine to train a public model for predicting user intent based on historical queries. Another significant patent is the "Unified attractiveness prediction framework based on content impact factor," which outlines a method for evaluating video content by extracting metadata and view data to calculate impact factor scores. This framework aims to identify videos with the highest potential for user engagement.

Career Highlights

Wanying Ding is currently employed at Tcl Research America Inc., where he continues to develop innovative solutions in his field. His work has garnered attention for its practical applications in understanding user intent and enhancing video content strategies.

Collaborations

Ding collaborates with talented individuals such as Lifan Guo and Haohong Wang, contributing to a dynamic research environment that fosters innovation and creativity.

Conclusion

Wanying Ding's contributions to user intent mining and video prediction exemplify the impact of innovative thinking in technology. His patents reflect a commitment to advancing the understanding of user behavior and improving content effectiveness in the digital landscape.