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For the Inventor, By the Inventor

Sunnyvale, CA, United States of America

Evgeniy Gabrilovich

This inventor holds 16 USPTO granted patents and 13 published patent applications and 1 EPO patent. Top assignees: Google Inc., Yahoo! Inc.. Active years: 2011-2022.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Evgeniy Gabrilovich. Retrieved from https://idiyas.com/inventor/evgeniy-gabrilovich

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 16 

% Patents Active = 62.5

 

Average Co-Inventor Count = 4.1

ph-index = 6

Forward Citations = 75(Granted Patents)


Location History:

  • Sunnyvale, CA (US) (2011 - 2021)
  • Saratoga, CA (US) (2018 - 2022)

Company Filing History:

goldMedal9 out of 33,959 
 
Google Inc.
 patents
silverMedal7 out of 2,367 
 
Yahoo! Inc.
 patents

Years Active: 2011-2022

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16 patents (USPTO):Explore Patents
1. 11526773 - Predicting accuracy of submitted data (2022-12-13),
2. 11475290 - Structured machine learning for improved whole-structure relevance of informational displays (2022-10-18),
3. 11138615 - Location-based place attribute prediction (2021-10-05),
4. 10977573 - Distantly supervised wrapper induction for semi-structured documents (2021-04-13),
5. 10452694 - Information extraction from question and answer websites (2019-10-22),
6. 10223637 - Predicting accuracy of submitted data (2019-03-05),
7. 10108700 - Question answering to populate knowledge base (2018-10-23),
8. 9875296 - Information extraction from question and answer websites (2018-01-23),
9. 9754036 - Adapting third party applications (2017-09-05),
10. 9129300 - Using external sources for sponsored search AD selection (2015-09-08),
11. 9015140 - System and method for providing contextual actions on a search results page (2015-04-21),
12. 8886636 - Context transfer in search advertising (2014-11-11),
13. 8812362 - Method and system for quantifying user interactions with web advertisements (2014-08-19),
14. 8676827 - Rare query expansion by web feature matching (2014-03-18),
15. 8521731 - Systems and methods for query expansion in sponsored search (2013-08-27),

Title: Evgeniy Gabrilovich: A Pioneer in Machine Learning and Data Accuracy Solutions

Introduction

Evgeniy Gabrilovich is an esteemed inventor hailing from Sunnyvale, CA, renowned for his contributions in the fields of machine learning and data accuracy. With a remarkable portfolio of 16 patents, Gabrilovich has dedicated his career to innovating solutions that enhance the way data is processed and displayed.

Latest Patents

Among his latest patents, Gabrilovich introduced groundbreaking methods and systems aimed at predicting the accuracy of user submissions. This innovative approach involves assessing a user's reliability based on their profile data before updating a knowledge base with relevant updates to an attribute of an entity. Additionally, he has developed patented systems that utilize machine learning to improve the relevance of hierarchical informational displays. This involves a sophisticated, supervised, discriminative machine learning methodology designed to optimize the ranking of items alongside their respective display attributes.

Career Highlights

Evgeniy Gabrilovich has had a distinguished career, contributing his expertise to notable companies like Google Inc. and Yahoo! Inc. His roles in these organizations have enabled him to push the boundaries of innovation, particularly within the realms of data processing and machine learning technologies.

Collaborations

During his career, Gabrilovich has collaborated with several talented professionals, including Vanja Josifovski and Andrei Z. Broder. Their combined efforts have led to significant advancements in the understanding and application of machine learning techniques.

Conclusion

Evgeniy Gabrilovich’s work exemplifies innovation and ingenuity within the rapidly evolving field of technology. Through his patents and collaborations, he continues to influence the development of methods that improve data accuracy and the functionality of informational displays, marking him as a pivotal figure in the domain of machine learning.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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