63 Google search and ranking patents by Paul Haahr, long-tenured Google search ranking engineer. Covers the canonical link-quality patents (Bharat/Singhal/Haahr "Determining quality of linked documents"), document-classification ranking, node-independence anti-PBN signal, the rumored quality-measure patent (cross-listed with 65gp pat-48), the multi-stage query processing pipeline, the framework for evaluating web search scoring functions (the documentary back-stop to his SMX talk), preferred sites, reference contexts, synthetic descriptive text for images, and the multi-family query refinement and stopword-detection clusters. Co-authored with Singhal, Dean, Bharat, Cutts, Henzinger, Simon Tong, and Acharya. Spans 2008 to 2019.
About the Paul Haahr, Google Search Patents track
63 Google search and ranking patents by Paul Haahr, long-tenured Google search ranking engineer. Covers the canonical link-quality patents (Bharat/Singhal/Haahr "Determining quality of linked documents"), document-classification ranking, node-independence anti-PBN signal, the rumored quality-measure patent (cross-listed with 65gp pat-48), the multi-stage query processing pipeline, the framework for evaluating web search scoring functions (the documentary back-stop to his SMX talk), preferred sites, reference contexts, synthetic descriptive text for images, and the multi-family query refinement and stopword-detection clusters. Co-authored with Singhal, Dean, Bharat, Cutts, Henzinger, Simon Tong, and Acharya. Spans 2008 to 2019.
Quality & Link-Based Ranking
- Determining Quality of Linked Documents (US 8,825,645 · September 2, 2014)
- Determining Quality of Linked Documents (2012) (US 8,176,056 · May 8, 2012)
- Determining Quality of Linked Documents (2010) (US 7,783,639 · August 24, 2010)
- Ranking Nodes in a Linked Database Based on Node Independence (US 8,719,276 · May 6, 2014)
- Determining a Quality Measure for a Resource (US 9,558,233 · January 31, 2017)
- Document Ranking Based on Document Classification (US 8,224,827 · July 17, 2012)
- Document Scoring Based on Document Inception Date (US 7,840,572 · November 23, 2010)
- Document Scoring Based on Document Inception Date (continuation) (US 8,521,749 · August 27, 2013)
- Document Scoring Based on Link-Based Criteria (US 8,407,231 · March 26, 2013)
- Information Retrieval Based on Historical Data (US 7,346,839 · March 18, 2008)
Query Processing & Refinement
- Document Scoring Based on Query Analysis (US 8,051,071 · November 1, 2011)
- Document Scoring Based on Query Analysis (2012a) (US 8,185,522 · May 22, 2012)
- Document Scoring Based on Query Analysis (2012b) (US 8,239,378 · August 7, 2012)
- Document Scoring Based on Query Analysis (2012c) (US 8,244,723 · August 14, 2012)
- Document Scoring Based on Query Analysis (2012d) (US 8,266,143 · September 11, 2012)
- Document Scoring Based on Query Analysis (2013) (US 8,577,901 · November 5, 2013)
- Document Scoring Based on Query Analysis (2014) (US 8,639,690 · January 28, 2014)
- Locating Meaningful Stopwords or Stop-Phrases in Keyword-Based Retrieval Systems (US 10,452,718 · October 22, 2019)
- Locating Meaningful Stopwords (2017) (US 9,817,920 · November 14, 2017)
- Locating Meaningful Stopwords (2015) (US 8,965,919 · February 24, 2015)
- Locating Meaningful Stopwords (2014) (US 8,626,787 · January 7, 2014)
- Locating Meaningful Stopwords (2013) (US 8,473,510 · June 25, 2013)
- Locating Meaningful Stopwords (2012) (US 8,214,385 · July 3, 2012)
- Locating Meaningful Stopwords (2011) (US 7,945,579 · May 17, 2011)
- Locating Meaningful Stopwords (earliest 2008) (US 7,409,383 · August 5, 2008)
- Systems and Methods for Providing Search Query Refinements (US 10,223,439 · March 5, 2019)
- Search Query Refinements (2017) (US 9,552,388 · January 24, 2017)
- Search Query Refinements (2016) (US 9,495,443 · November 15, 2016)
- Search Query Refinements (2014) (US 8,645,407 · February 4, 2014)
- Search Query Refinements (2013) (US 8,504,584 · August 6, 2013)
- Search Query Refinements (2011b) (US 8,086,619 · December 27, 2011)
- Search Query Refinements (2011a) (US 8,065,316 · November 22, 2011)
- Providing Result-Based Query Suggestions (US 10,459,989 · October 29, 2019)
- Result-Based Query Suggestions (2017) (US 9,563,692 · February 7, 2017)
- Result-Based Query Suggestions (2015) (US 9,092,528 · July 28, 2015)
- Result-Based Query Suggestions (2013) (US 8,583,675 · November 12, 2013)
- Multi-Stage Query Processing System and Method for Use with Tokenspace Repository (US 9,146,967 · September 29, 2015)
- Multi-Stage Query Processing (2013) (US 8,407,239 · March 26, 2013)
- Query Generation Using Structural Similarity Between Documents (US 9,436,747 · September 6, 2016)
- Query Generation Structural Similarity (2015) (US 9,092,479 · July 28, 2015)
- Query Generation Structural Similarity (2013) (US 8,346,792 · January 1, 2013)
Site Signals & Quality Infrastructure
- Document Scoring Based on Document Content Update (US 8,112,426 · February 7, 2012)
- Document Scoring Content Update (2012) (US 8,234,273 · July 31, 2012)
- Document Scoring Content Update (2013a) (US 8,527,524 · September 3, 2013)
- Document Scoring Content Update (2013b) (US 8,549,014 · October 1, 2013)
- Preferred Sites (US 10,025,868 · July 17, 2018)
- Preferred Sites (2016) (US 9,317,563 · April 19, 2016)
- Preferred Sites (2013) (US 8,595,228 · November 26, 2013)
- Ranking Based on Reference Contexts (US 8,577,893 · November 5, 2013)
- Propagating Information Among Web Pages (US 8,990,210 · March 24, 2015)
- Propagating Information (2013) (US 8,521,717 · August 27, 2013)
- Propagating Useful Information Among Related Web Pages (US 7,933,890 · April 26, 2011)
- Using Synthetic Descriptive Text to Rank Search Results (US 9,208,233 · December 8, 2015)
- Generating Synthetic Descriptive Text (US 9,208,232 · December 8, 2015)
- Generating Descriptive Text for Images Using Seed Descriptors (2018) (US 9,971,790 · May 15, 2018)
- Generating Descriptive Text for Images Using Seed Descriptors (2019) (US 10,248,662 · April 2, 2019)
- Framework for Evaluating Web Search Scoring Functions (US 8,572,075 · October 29, 2013)
- Framework for Evaluating Web Search Scoring Functions (2011) (US 8,060,497 · November 15, 2011)
- Automated Resource Selection Process Evaluation (US 8,489,604 · July 16, 2013)
- Embedded Communication of Link Information (US 8,260,766 · September 4, 2012)
- Embedded Communication of Link Information (2011) (US 7,979,417 · July 12, 2011)
- Personally Identifiable Information Detection (US 9,015,802 · April 21, 2015)
- Personally Identifiable Information Detection (2013) (US 8,561,185 · October 15, 2013)
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.