Company Filing History:
Years Active: 2020-2021
Title: Yumei Tung: Innovator in Cardinality Estimation Technologies
Introduction
Yumei Tung is a notable inventor based in Vienna, VA (US), recognized for her contributions to the field of data estimation technologies. With a total of 2 patents, she has made significant strides in optimizing cardinality estimation methods for big data applications.
Latest Patents
Yumei Tung's latest patents include innovative systems and methods for optimizing full-spectrum cardinality approximations. The first patent, titled "Optimized full-spectrum order statistics-based cardinality estimation," discloses techniques for accurately determining cardinality estimates using an optimized order statistics approach. This method involves obtaining a multiset of objects and processing a compound data object populated with data derived from generated decimal fraction hash values. The result is a more efficient estimation process that requires fewer resources and less time compared to traditional techniques.
The second patent, "Optimized full-spectrum loglog-based cardinality estimation," focuses on utilizing an optimized LogLog counting technique. Similar to her first patent, this invention also involves obtaining a multiset of objects and processing a compound data object populated with hash values. The full-spectrum harmonic mean estimation operation allows for accurate cardinality estimates while avoiding the need for linear counting or bias correction operations.
Career Highlights
Yumei Tung is currently employed at Verizon Media Inc., where she continues to develop and refine her innovative technologies. Her work has positioned her as a key player in the field of data estimation, contributing to advancements that benefit various industries reliant on big data analytics.
Collaborations
Yumei has collaborated with notable coworkers, including Jason Jinshui Qin and Denys P Kim, further enhancing her work through shared expertise and innovative ideas.
Conclusion
Yumei Tung's contributions to cardinality estimation technologies reflect her dedication to advancing data analytics. Her patents demonstrate a commitment to optimizing processes that are crucial for handling big data efficiently.
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