A curated collection of foundational and advanced patents filed by Google.
About the 65 Google Patents to Help You Understand How Search Engines Work! track
A curated collection of foundational and advanced patents filed by Google.
Foundational Semantic Search Patents
- Information Extraction from a Database (DIPRE Algorithm) (US 6,678,681 · January 13, 2004)
- Semantic Search (Original) (US 20090070312A1)
Phrase-Based Indexing Patents
- Phrase-Based Indexing in an Information Retrieval System (US 7,536,408 · May 19, 2009)
- Phrase-Based Detection of Duplicate Documents (US 7,711,679 · May 4, 2010)
- Information Retrieval System for Archiving Multiple Document Versions (US 7,702,618 · April 20, 2010)
- Detecting Spam Documents in a Phrase-Based Information Retrieval System (US 7,603,345 · October 13, 2009)
- Phrase-Based Searching in an Information Retrieval System (US 7,599,914 · October 6, 2009)
- Phrase-Based Generation of Document Descriptions (US 7,584,175 · September 1, 2009)
- Phrase-Based Personalization of Searches (US 7,580,929 B1 · August 25, 2009)
- Phrase Identification in Information Retrieval Systems (US 7,580,921 B2 · August 25, 2009)
- Multiple Index Based Information Retrieval System (US 7,567,959 · July 28, 2009)
- Automatic Taxonomy Generation in Search Results Using Phrases (US 7,426,507)
- Index Server Architecture Using Tiered and Sharded Phrase Posting Lists (US 7,693,813)
- Index Updating Using Segment Swapping (US 7,702,614)
- Query Scheduling Using Hierarchical Tiers of Index Servers (US 7,925,655)
- Integrating External Related Phrase Information (US 20090070312A1)
- Detecting Spam Documents (Updated) (US8078629B2 · December 13, 2011)
Entity & Knowledge Graph Patents
- Knowledge Graph Based Search System (US 20120158633A1)
- Systems and Methods for Ranking Content Using Entity-Based Metrics (US 20180046834A1 (2018))
- Identifying Salient Entities in Text (US 20150127617A1 (2015))
- Entity Recognition/Identification Model Training (US 9,251,141 · February 2, 2016)
- Contextual Search Based on Entity Relationships (US 20150370804A1 (2015))
- Query Categorization Based on Entities (US 10169351B1 (2019))
- Ranking Search Results Based on Entity Centrality (US 20160232149A1 (2016))
- Word Sense Disambiguation Using Entity Graphs (US US11687724)
- Generating Structured Information from Unstructured Text (US 20140143273A1 (2014))
- Enterprise Knowledge Graphs Using User-Based Mining (US 20220019908A1)
- Search in Knowledge Graphs (US 12254033B2)
- Searching Quotes of Entities
- Identifying Entity Attribute Relations ( · March 1, 2022)
Query Understanding & Intent Patents
- Evaluating an Interpretation for a Search Query (US 20230334045A1)
- Refining Search Queries
- Query-Dependent Ranking Factors (US 9218397B1)
- Processing and Editing Natural Language Queries
- Natural Language Search Results for Intent Queries (EP3005168A1)
- Contextual Estimation of Link Information Gain (WO2020081082)
- Combining Parameters of Multiple Search Queries (US 11762848B2)
- Query Composition System (US 20230244657A1)
Content Quality & Site Authority Patents
- High Quality Sites Patent (Panda) (US 9,135,307 · September 15, 2015)
- Predicting Site Quality (N-gram Analysis) (US 9,767,157)
- Content Clustering (US 10108694)
- Context Scoring Adjustments for Answer Passages (https)
- Topicality Scores, Social Scores and User-Generated Content
PageRank & Link Analysis Patents
- PageRank (Original) (US 6,285,999B1)
- Reasonable Surfer Model (US 8,117,209B1 / US 7,716,225)
- Producing a Ranking for Pages Using Distances in a Web-Link Graph (US 9165040B1)
- Agent Rank (US 7,565,358B2 · 2009)
- Determining a Quality Measure for a Resource (US 9,558,233B1 · January 31, 2017)
- Ranking Documents Based on User Behavior and/or Feature Data (US 7,716,225B1)
User Behavior & Ranking Signal Patents
- Document Scoring Based on Document Inception Date (US 8,521,749B2)
- Historical Data Patent (US 7,346,839B2)
- Watch Time Based Ranking (US 9,098,511)
- Website Duration Performance (US 9,514,194)
- Modifying Search Result Ranking Based on Implicit User Feedback (US 8,661,029B1)
- Click-Through Rate as a Ranking Factor (US 10,229,166B1)
- User-Context-Based Search Engine (US 9,449,105B1)
- Personalized Search (US 8,762,373B1)
Recent Patents (2023+)
- Search Result Filters from Resource Content (US 11797626B2 · October 2023)
- Providing Search Results Based on Compositional Query (US 11762933B2 · September 2023)
- Contextualizing Knowledge Panels (US 11720577B2 · August 2023)
- Document Activity Logs for Machine Learning (US 20230267277A1 · August 2023)
- Multi-Source Extraction and Scoring of Short Query Answers (US 20230342411A1 · October 2023)
- Presenting Search Result Information (Web Notebooks) (US 11775535B2 · October 2023)
- BERT Question-Answering ( · May 2021)
Other Notable Patents (Adjacent Ecosystem)
- Reader Apparatus for Upconverting Nanoparticle Ink Printed Images
- Digital Aging System
- Effects Application Based on Object Clustering (US 2015/0370804 A1 · 2015)
- Smart Optical Input/Output Extension
- Enhanced Information Search System ( · 2014)
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.