23 Google search and ranking patents by Hyung-Jin Kim. Lead inventor on the Navboost / implicit-feedback ranking family (US 8,661,029 + 5 continuations through US 11,816,114 active 2023 IP), the system surfaced at the 2024 DOJ Google antitrust trial. Also covers the presentation-bias model, temporal score adjustments, document-change ranking, user cohort grouping, similar-query borrowing, variant generalized queries, propagating query classifications, and the cross-listed Quality Measure patent (with Paul Haahr, 65gp pat-48). Co-authored with Simon Tong, Noam Shazeer, Michelangelo Diligenti, Adrian Corduneanu, Henele Adams, Andrei Lopatenko. Filings 2006-2021.
About the Hyung-Jin Kim, Google Search Patents track
23 Google search and ranking patents by Hyung-Jin Kim. Lead inventor on the Navboost / implicit-feedback ranking family (US 8,661,029 + 5 continuations through US 11,816,114 active 2023 IP), the system surfaced at the 2024 DOJ Google antitrust trial. Also covers the presentation-bias model, temporal score adjustments, document-change ranking, user cohort grouping, similar-query borrowing, variant generalized queries, propagating query classifications, and the cross-listed Quality Measure patent (with Paul Haahr, 65gp pat-48). Co-authored with Simon Tong, Noam Shazeer, Michelangelo Diligenti, Adrian Corduneanu, Henele Adams, Andrei Lopatenko. Filings 2006-2021.
Implicit Feedback & Click-Driven Ranking
- Modifying Search Result Ranking Based on Implicit User Feedback (US 8,661,029 · February 25, 2014)
- Modifying Search Result Ranking (continuation 2016) (US 9,235,627 · January 12, 2016)
- Modifying Search Result Ranking (continuation 2017) (US 9,811,566 · November 7, 2017)
- Modifying Search Result Ranking (continuation 2019) (US 10,229,166 · March 12, 2019)
- Modifying Search Result Ranking (continuation 2021) (US 11,188,544 · November 30, 2021)
- Modifying Search Result Ranking (continuation 2023) (US 11,816,114 · November 14, 2023)
- Modifying Search Result Ranking Based on Implicit User Feedback and a Model of Presentation Bias (US 8,938,463 · January 20, 2015)
- Combining User Feedback (US 8,832,083 · September 9, 2014)
- Accentuating Search Results (US 9,623,119 · April 18, 2017)
Quality, Temporal & User-Cohort Ranking
- Determining a Quality Measure for a Resource (US 9,558,233 · January 31, 2017)
- Temporal-Based Score Adjustments (US 8,924,379 · December 30, 2014)
- Modifying Scoring Data Based on Historical Changes (US 8,898,153 · November 25, 2014)
- Modifying Ranking Data Based on Document Changes (US 9,002,867 · April 7, 2015)
- Grouping of Users (US 8,930,351 · January 6, 2015)
- Refining Search Results (US 9,697,259 · July 4, 2017)
- Determining Resource Quality Based on Resource Competition (US 9,020,927 · April 28, 2015)
- Determining Codomain Relationship Measures (US 8,943,099 · January 27, 2015)
Query Classification & Similarity
- Ranking Search Results Based on Similar Queries (US 9,009,146 · April 14, 2015)
- Search Result Inputs Using Variant Generalized Queries (US 9,110,975 · August 18, 2015)
- Propagating Query Classifications (US 9,659,097 · May 23, 2017)
- Autocompletion Using Previously Submitted Query Data (US 9,740,780 · August 22, 2017)
- Enhanced Identification of Interesting Points-of-Interest (US 9,057,616 · June 16, 2015)
- Identifying Landing Pages for Images (US App 2015/0161120 · June 11, 2015)
Why this inventor matters
Each inventor track inside the Nizam SEO War Room patents archive isolates one engineer's research arc — typically a decade or more of continuations, divisionals, and follow-up patents on a coherent research thread. Reading by inventor (rather than by topic) recovers the narrative: how the original disclosure evolved, what the continuations added, which claims got carved out into divisional applications, and how the thread eventually intersected with other research lines at Google or Microsoft. This is how working SEOs build durable intuition about search-engine internals — not by memorizing claim language, but by following the research bibliography that shipped the algorithms we now optimize against.
How to read this track
Start with the earliest filing — it sets the foundational disclosure. Continuations refine the claims; divisional applications split out separable inventions; the follow-up patents tend to introduce performance optimizations, edge-case handling, or downstream integration with other systems. Each patent on this site is annotated with the ranking surface it touches — query understanding, document retrieval, ranking, behavioral signals, knowledge graph, or AI search — so the practitioner can map the research back to the algorithm output observed on live SERPs.