Company Filing History:
Years Active: 2020-2021
Title: Innovations by Jason Jinshui Qin
Introduction
Jason Jinshui Qin is an accomplished inventor based in Great Falls, VA (US). He has made significant contributions to the field of data estimation and optimization, holding a total of 3 patents. His work focuses on enhancing the efficiency of cardinality estimation techniques, particularly in the context of big data.
Latest Patents
One of his latest patents is titled "Optimized full-spectrum order statistics-based cardinality estimation." This patent discloses systems and methods for optimizing full-spectrum cardinality approximations on big data by utilizing an optimized order statistics technique. The process involves obtaining a multiset of objects corresponding to various resources and populating a compound data object with data derived from generated decimal fraction hash values. The method allows for accurate cardinality estimates with reduced resource usage and time compared to traditional techniques.
Another notable patent is "Optimized full-spectrum cardinality estimation based on unified counting and ordering estimation techniques." This invention optimizes full-spectrum cardinality approximations by exploiting the relationship between LogLog counting estimation techniques and order statistics-based estimation techniques. The computing device processes a populated compound data object to determine cardinality estimates while minimizing memory usage and improving performance.
Career Highlights
Jason is currently employed at Verizon Media Inc., where he continues to innovate and develop advanced data estimation techniques. His work has positioned him as a key contributor in the field of data analytics and optimization.
Collaborations
He collaborates with talented coworkers, including Denys P Kim and Yumei Tung, who contribute to the innovative environment at Verizon Media Inc.
Conclusion
Jason Jinshui Qin's contributions to the field of data estimation through his patents demonstrate his commitment to innovation and efficiency. His work continues to influence the way big data is processed and analyzed.
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