Google Patents Archive

A curated archive of Google and Microsoft search patents organized by the inventor or research lead who shipped them. Each track follows one engineer through their patent lineage so the reader can see how a research thread evolved across continuations, divisional applications, and grants. Patents are annotated with the ranking surface they touch — query understanding, ranking, retrieval, behavioral signals, knowledge graph, or AI search.

Patent tracks by inventor

• 65 Google Patents to Help You Understand How Search Engines Work! (69 patents) — A curated collection of foundational and advanced patents filed by Google.
• Steven Baker — Google Search Patents (49 patents) — 49 granted search-engine patents plus 2 published applications by Google researcher Steven D. Baker, covering query understanding (synonyms, n-gram, geographic, cross-language), query refinement, meaningful stopword detection, answer passage scoring (featured snippets), query–document similarity, list co-occurrence, and embedding-based personalized search.
• Amit Singhal — Google Search Patents (22 patents) — 22 search-engine patents by Amit Singhal, former Google SVP of Search (2000-2016), covering interleaving and result composition, query rewriting, semantic query understanding, link-quality scoring, location-aware ranking, language and country biasing, commercial-intent detection, and advertisement serving. The 8-patent meaningful-stopwords family is co-invented with Steven Baker and is documented under the Steven Baker section to avoid duplicate content.
• Prabhakar Raghavan — Google Search Patents (16 patents) — 16 search/IR patents by Prabhakar Raghavan, head of Google Search 2020-2024 (previously Yahoo VP and IBM Almaden research scientist), covering personalized PageRank, web community detection, adaptive ranking, multi-engine result merging, hierarchical taxonomy, subspace clustering, information filtering, customizable navigation, user-generated content surfacing, location-quality signals from travel patterns, and temporal metadata analysis. Spans his IBM, Yahoo, and Google research.
• Nitin Gupta — Google Search Patents (32 patents) — 32 search/SEO patents by Nitin Gupta (Google Search Quality engineer) covering query suggestions and templates, reranking and personalization, answer-generating neural networks, content-knowledge generation, the latest 2026 generative-search retrieval patent for the AI Overviews era, and a direct SEO patent on domain names and websites. The final 5 patents are co-invented with Steven Baker and are documented in his section to avoid duplicate content.
• Navneet Panda — Google Search Patents (15 patents) — 15 search-quality patents by Navneet Panda, the Google engineer whose content-quality work became the basis for the Panda algorithm update (2011). Covers site quality scoring, predicting site quality before behavioral data accumulates, ranking search results by combined relevance and site-quality signals, website duration performance, locally significant queries, query revision, and image-concept learning.
• Anand Shukla — Google Search Patents (16 patents) — 16 search/IR patents by Anand Shukla, Google Search Quality engineer, including the cutting-edge 2024 "Search with stateful chat" patent that bridges classical search to LLM-based conversational search. Also covers in-depth article surfacing, query pattern matching, query topic mapping, content channel curation, and the enhanced-search-feed family. The final 3 patents are co-invented with Steven Baker on the personalized-feed embeddings work and are documented in his section.
• Krishna Bharat, Google Search Patents (48 patents) — 48 search-engine patents by Krishna Bharat, founding inventor of Google News and creator of the Hilltop algorithm. Covers the Hilltop link-analysis algorithm, query rewriting with entity detection, semantic units in queries, query and search augmentation, document ranking by usage statistics, image selection for news search, editorial-opinion ranking, search engine coverage estimation, query-specific bookmarking, and entity-aware ad rendering. Spans 2001 to 2024.
• Srinivasan Venkatachary, Google Search Patents (25 patents) — 26 search-engineering patents by Srinivasan Venkatachary, co-inventor on the Generative Summaries for Search Results patent family that underpins AI Overviews and Search Generative Experience. Also covers enhanced search feeds based on user interests, candidate-answer-passage scoring, context-scoring adjustments for answer passages, implicit question query identification, keyword-based conversational voice search, query generation via document structural similarity, resource identification from organic and structured content, content channel curation, and the emoji classifier. Spans 2013 to 2025.
• Jeromy William Henry, Google Search Patents (25 patents) — 25 search-engine patents by Jeromy William Henry covering Knowledge Panels (the entity card next to search results), Structured Entity Information Pages (the standalone entity-detail surface), Personalized Entity Information Pages, SERP image sizing, and music-search secondary link presentation. Every patent in his corpus is SEO-relevant. Spans 2013 to 2025.
• Ramanathan V. Guha, Google Search Patents (33 patents) — 33 search-engine patents by Ramanathan V. Guha, co-founder of Schema.org and lead inventor on Google Custom Search Engine. Covers the Programmable Search Engine family, trust-based search ranking, spam detection for programmable contexts, social-signal propagation, classifying search results, customized web summaries, filtering by user annotations, contextual searching by query intersections, query identification, and the generating-tasks UI family. Spans 2003 to 2019.
• Marc Najork, Google Search Patents (25 patents) — 25 search/IR patents by Marc Najork spanning his Microsoft Research era (web crawler architecture, spam-resistant ranking, content evaluation, hyperlink databases) and his Google era (form information extraction, ML-driven semantic similarity, active learning, document activity logs for relevance training). Includes a foundational cross-listed patent with the 65 Google Patents collection on document activity logs. Spans 2005 to 2025.
• Jeffrey Dean, Google Search Patents (78 patents) — 78 search and IR-infrastructure patents by Jeffrey Dean, Google Senior Fellow and Chief Scientist, co-founder of Google Brain, and architect of MapReduce and BigTable. Includes the foundational Document Scoring families (Query Analysis, Content Update, Inception Date, Link-Based Criteria), Historical Data Patent (cross-listed with 65gp), Anchor Tag Indexing, Content Snippets via Tokenspace, near-duplicate and mirrored-host detection, topic-drift prevention, distributed ML models, and the foundational MapReduce and BigTable infrastructure that makes web-scale search possible. Spans 2000 to 2025.
• Paul Haahr, Google Search Patents (63 patents) — 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.
• Hyung-Jin Kim, Google Search Patents (23 patents) — 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.
• Pandu Nayak, Google Search Patents (13 patents) — 13 Google search patents by P. Pandurang Nayak, Google Chief Scientist for Search. The patent record covers the query-revision and query-understanding stack from 2003-2015: integration of multiple query-revision models, confidence-scored revision, known-highly-ranked-queries borrowing, concept-context substitution, phrase-restricted synonyms, click-driven synonym identification, acronym expansion. Co-authored with David R. Bailey, Ben Gomes, Trystan Upstill, Kedar Dhamdhere, Thomas Strohmann. His neural-era contributions (RankBrain, BERT, MUM, DOJ testimony) are intentionally unpatented and live in blog posts and trial transcripts.
• Daniel Egnor, Google Local Search Patents (20 patents) — 20 Google local-search and geographic-relevance patents by Daniel Egnor, the architect of the Google Maps / Local Pack ranking layer. Lead inventor on US 8,046,371 "Scoring local search results based on location prominence" — the patent that defines the "Prominence" factor in Google's official Local Search Ranking documentation. Also covers location-sensitivity ranking (Relevance factor, with Amit Singhal), geographical-relevance indexing, ambiguous-geographic-reference resolution, authoritative-document identification, business-listing categorization, and GIS ambiguous-search processing (with Keyhole founder John Hanke). Co-authored with Singhal, Haahr, Greenfield, John Hanke. Filings 2003-2019.
• Yossi Matias, Google SERP Features & Assistant Patents (47 patents) — 47 Google patents by Yossi Matias, Google VP Engineering. Lead inventor on the foundational People-Also-Ask patent US 9,213,748 "Generating related questions for search queries". Built Autocomplete (2004), Trends, weather/sports/dictionary OneBoxes. Covers the People-Also-Ask family, Knowledge Panel entity scaffolding (grouping related entities, central-entity identification, fact estimation, textual entity attributes, entity-quote search), the Trends/analytics layer (campaign-competitive analysis, ranking graphical visualizations), the Duplex automated-call infrastructure, the personalized chatbot and LLM-output entailment patents that underpin Google Assistant's 2024-2026 generative era, and contextual / third-party SERP-features. Co-authored with Yaniv Leviathan (Duplex), Gal Chechik, Ziv Bar-Yossef, Eyal Segalis, Avinatan Hassidim. Filings 2013-2026.
• Andrei Broder, Cross-Vendor Search Patents (25 patents) — 25 search-engine and IR patents by Andrei Broder, the cross-vendor inventor who shaped near-duplicate detection at DEC/AltaVista, co-invented the foundational CAPTCHA at Compaq, built the AltaVista web-page ranking system, authored web-page-decay signal at IBM, and shaped ad-matching/SERP-features/CAPTCHA-evolution infrastructure at Yahoo. Lead inventor on the foundational MinHash/shingling patent (US 6,349,296), the fingerprint-collision-probability technique (US 5,974,481), the document-resemblance shingling patent (US 6,230,155), and the foundational CAPTCHA patent (US 6,195,698). Spans 1999 to 2024.
• Monika Henzinger, Google Search Patents (50 patents) — 98 search and IR patents by Monika Henzinger, the first Director of Research at Google. Co-inventor on the foundational near-duplicate-page-detection patent (US 6,138,113, with Dean) and an extensive set of document-scoring families (Query Analysis, Content Update, Inception Date, Link-Based Criteria, Historical Data — all cross-listed with Dean's canonical articles). Independent contributions: the detecting-duplicate-files family with William Pugh, the AltaVista connectivity-server, the connectivity-and-content-ranking patents, document-freshness determination, semantic-distance ranking, query-semantic-information ranking, anchor-text cross-language IR, in-context searching, hypertext-browser assistant, and usage-statistics-driven document retrieval. Spans 1997 to 2017.
• Trystan Upstill, Google Site-Quality & HCU-Era Search Patents (28 patents) — 28 Google search and ranking patents by Trystan Upstill. Co-inventor on the Panda patent (US 9,135,307 = 65gp pat-39) and lead inventor on the HCU-era follow-up US App 2019/0155948 "Re-ranking resources based on categorical quality" — the patent that anchors the post-Panda site-quality lineage. Also covers authoritative-results discovery, search-result ranking and re-scoring, affiliated-domains detection, resource-attribute extraction from site address, local search and POI identification, synonyms and query rewriting, navigational-intent resources, language identification from link context, and the recent LLM-era UI components patent. Filings 2012-2026.
• Susan Dumais, Microsoft IR & Search Patents (18 patents) — 61 search and IR patents by Susan Dumais, Microsoft Technical Fellow and Gerard Salton Award winner. Co-inventor on the foundational Latent Semantic Indexing patent (US 4,839,853, Bellcore 1989) — the conceptual ancestor of every dense-embedding retrieval system. At Microsoft Research her work covers automated SERP satisfaction measurement, preference-judgment click models, activity-based-context ranking, time-aware ranking with temporal dynamics, personalized navigation and search results, per-user domain-expertise determination, web-page-change × revisitation freshness, implicit device-related query reformulation, authority ranking. Spans 1989 to 2026. Co-authors include Jaime Teevan, Eric Horvitz, Ryen White, Adam Fourney, Joshua Goodman, Eric Brill.
• Christopher Burges, Microsoft Research Learning-to-Rank Patents (16 patents) — ~30 unique US inventions (84-entry WIPO corpus) by Christopher J. C. Burges, the Microsoft Research scientist who invented the RankNet/LambdaRank/LambdaMART learning-to-rank lineage. RankNet (US 7,689,615) is the pairwise neural ranker; LambdaRank (US 7,617,164) is the arbitrary-cost extension that optimizes NDCG; LambdaMART (US 12/032,697) is the gradient-boosted ensemble that won the Yahoo LTR Challenge 2010. Also covers behavioral-variability adaptation, web-page multi-graph analysis, link-spam smoothing, margin-tree boosting, k-NN probability estimation. Spans 2001 to 2019. Co-authors include Robert Ragno (LambdaRank), Irina Matveeva, Timo Burkard.
• Eric Brill, Microsoft Research Search & NLP Patents (20 patents) — 20 Microsoft Research patents by Eric Brill, the NLP and search scientist known for query speller patents and the noisy-channel correction model. Lead inventor on US 7,254,774 "Systems and methods for improved spell checking" — the foundational noisy-channel query speller patent. Also covers string-to-string spell-correction transformations (US 7,290,209 / 7,366,983), behavioral-variability accounting in web search (US 7,743,047), popularity-data ranking, mining web search user behavior, page-biased search, cost-benefit Q&A composition, and user-intent discovery. Filings 2005-2010.
• Tomas Mikolov, Google word2vec Patents (2 patents) — 2 foundational Google patents by Tomas Mikolov covering word2vec — the continuous word-embedding learning model that defined the embeddings era. Co-invented with Kai Chen, Greg Corrado, and Jeff Dean. US 9,037,464 is the original grant; US 9,740,680 is the continuation with broader claim scope. Both patents share the same disclosure (application 13/841,640) and together constitute the entire word2vec patent family. Cross-listed conceptually with Dean's section (Dean is co-inventor and works on the broader Brain/distributed-models infrastructure).
• Noam Shazeer, Google Transformer, MoE & Search Patents (18 patents) — ~46 captured Google patents (full portfolio estimated at 120-150) by Noam Shazeer. Co-inventor on the foundational Transformer attention architecture (US 10,452,978 with Vaswani, Polosukhin, Uszkoreit, Jones, Gomez, Kaiser, Parmar), the Sparsely-Gated Mixture-of-Experts scaling approach (US 11,769,055 with Dean, Hinton, Le, Mirhoseini), the Switch Transformer (US 12,093,829), and the Navboost implicit-feedback ranking family (US 8,661,029 with Kim/Tong/Diligenti — cross-listed). Also covers LLM-in-assistant response generation, distributed tensor computations (GSPMD/Pathways), and the 2008-2015 pre-Transformer large-scale ML ranking infrastructure. Spans 2008 to 2025.
• Ashish Vaswani, Google Transformer, Attention-Based Vision & Fast Decoding Patents (6 patents) — 4 captured new canonical articles plus 2 cross-listings from the Noam Shazeer section. Lead author of the foundational Transformer patent (US 10,452,978, cross-listed). First inventor on the local-self-attention computer vision patent (US 20210390410, HaloNet) that scales attention to long sequences and images. Co-inventor on MultiModel (US 20200089755 — the unified multi-task multi-modal architecture that is the structural ancestor of MUM and Gemini), the fully-attentional computer vision system (US 20250292560, the ViT lineage), and the fast-decoding-with-discrete-latents method (EP 3732627) that makes LLM inference economically viable at search-scale latency. Spans 2017 to 2025.
• Jakob Uszkoreit, Google Transformer Architect, Universal Transformer & Vision Transformer Patents (6 patents) — 3 new canonical articles plus 3 cross-listings from the Vaswani and Shazeer sections. Co-author of "Attention Is All You Need" (US 10,452,978, cross-listed). Co-inventor on the Universal Transformer (US 10,740,433, the adaptive-depth Transformer with per-token Adaptive Computation Time), the Decomposable Attention NLI model (EMNLP 2016, the load-bearing pre-Transformer proof that attend-compare-aggregate replaces recurrence), and the Vision Transformer (ViT, ICLR 2021, the patch-tokenization architecture that anchors modern visual search and multimodal grounding). Cross-listings cover the original Transformer, MultiModel (the unified multi-task multi-modal ancestor of MUM/Gemini), and the Image Transformer. Spans 2016 to 2021.
• Simon Tong, Google Click-Driven Ranking, Population Signals & Anti-Spam Patents (9 patents) — 5 new canonical articles plus 4 cross-listings from the Kim, Shazeer, and 65 Google Patents sections. Tong is co-inventor with Marc Pearson and Sergey Brin on the related-query ranking patent (US 7,505,964), with Pearson on the population-information ranking patent (US 7,454,417), solo on country biasing (US 20040254932), with Bem/Harik/Levenberg/Shazeer on the pre-Transformer large-scale ML ranking infrastructure (US 7,222,127), and with Ghemawat/Piscitello/Cutts on the user-document-removal patent (US 8,417,697, the structural ancestor of Personal Blocklist and crowd-sourced spam signals). Cross-listings cover the Navboost implicit-feedback family, the CTR-as-ranking-factor patent, the historical-data patent, and the large-dataset-ranking continuation. Spans 2003 to 2017+.
• Michelangelo Diligenti, Google Click-Data Quality & Implicit Feedback Patents (5 patents) — 2 new canonical articles plus 3 cross-listings from the Kim and 65 Google Patents sections. Diligenti is inventor on the Detecting Click Spam patent (US 8,694,374, attribute-deviance anomaly detection feeding ranking signal) and on the Click Model That Accounts for User Intent (US 20120143789, intent-conditional click weighting). His Navboost / presentation-bias / CTR-as-ranking-factor co-inventorships (cross-listed) anchor him in the implicit-feedback ranking family. The portfolio focuses on click-data quality, the layer between raw user behavior and the ranking signal it feeds. Spans 2007 to 2019+.
• Jaime Teevan, Microsoft Personalized Search & Search-Task Patents (5 patents) — 4 new canonical articles plus 1 cross-listing from the Dumais section. Teevan is co-inventor with Dumais and Horvitz on the foundational personalized-search patent (US 7,693,818) that re-ranks global candidates against a per-user profile vector. Inventor on search-task identification (US 8,326,824, cross-session query clustering into multi-step tasks), on re-finding vs new-finding classification (US 8,756,219, stabilizing prior clicked results for return visits), and on microtask search decomposition (US 10,062,103, decomposing high-level goals into resumable micro-steps). Cross-listing covers personalized-navigation (Dumais canonical). Spans 2003 to 2018+.
• Eric Horvitz, Microsoft Decision-Theoretic Search & Attention-Aware Information Delivery Patents (3 patents) — 3 new canonical articles. Horvitz is inventor on decision-theoretic ranking under uncertainty (US 7,124,129, relevance as a probability distribution with expected-utility selection), on cost-benefit reasoning in search-result presentation (US 7,194,464, the mechanical basis for featured snippets and AI Overviews), and on attention-aware proactive information delivery (US 6,934,917, the zero-query surfaces lineage behind Discover, Now cards, and AI assistants). Spans 2002 to 2006+.
• Ryen White, Microsoft Search Behavior & Search-Trails Patents (3 patents) — 3 new canonical articles. White is inventor on search-trail / successful-path mining (US 7,904,440, ranking destinations that end successful cross-user trails), on exploratory-versus-lookup query phase classification (US 8,041,711, serving phase-tuned ranking and result formats), and on cross-session task continuation (US 9,116,996, stitching queries across sessions and devices into one continuing task). Spans 2007 to 2015+.
• Azalia Mirhoseini, Google ML Infrastructure & Chip-Design Patents (3 patents) — 2 new canonical articles plus 1 cross-listing from the Shazeer section. Mirhoseini is co-inventor on the RL-based chip floorplan placement patent (US 11,475,278, the Nature 2021 paper that designs TPU floorplans in hours instead of weeks) and on the device-placement-for-distributed-ML patent (arXiv 1706.04972, the RL controller that learns how to split large models across GPUs/TPUs to minimize training time). Both feed back into the compute-cost economics that let Google serve Transformer ranking at search-scale. Cross-listing covers the foundational MoE patent (Shazeer canonical). Spans 2017 to 2021+.
• Arnold Overwijk, Microsoft Site Topical Authority Patent (1 patents) — 1 canonical article. Overwijk is co-inventor with Li Xiong, Chuan Hu, and Junaid Ahmed on the Site Topical Authority patent (US 20210004416, the formula A(s,t) = SR(s) * C(s) * T(s,t)^2 that explicitly quantifies per-site per-topic authority by combining global site rank, click signal, and squared per-topic page share). The most precise mathematical formulation of topical authority in the modern patent literature. Conceptually paired with Procopio (per-author per-topic authority) and Agent Rank (author-level reputation, 65gp pat-47).
• Michael Procopio, Google Per-Author Per-Topic Authority Patent (1 patents) — 1 canonical article. Procopio is named inventor on the Topic Authority patent (US 8,458,196). The system computes per (author, topic) authority signatures: for each document d the author contributed to, sum (authorship% * topic_weight); aggregate across all the author's documents to produce a per-author per-topic expertise score. The mathematical quantification of "this person is an authority on this topic," structurally the basis for the E-A-T Expertise signal at the author level. Connects to Agent Rank (US 7,565,358, 65gp pat-47, the earlier Google author-reputation patent) and to Overwijk's site-topical-authority (US 20210004416) to form a layered authority model.
• Ori Allon, Google Orion Query-Refinement Patent (1 patents) — 1 canonical article. Allon is co-inventor on the Orion query-refinement patent (US 8,392,443) with Ugo Di Girolamo, Tomer Shmiel, Alexandre Petcherski, and Tzvika Hartman. The Orion algorithm originated as Allon's PhD-thesis work at UNSW and was acquired by Google in 2006. The patent generates corpus-mined query refinements: given a query, extract phrase patterns from documents that satisfy the query to produce ranked refinement candidates. The mechanism behind "Searches related to," extended SERP snippets, and the lineage of People-Also-Ask. Granted 2013.
• Corin Anderson, Google Reasonable Surfer (Foundational) Patent (2 patents) — 1 new canonical article plus implicit cross-listings to the 65 Google Patents collection. Anderson is FIRST inventor on the foundational Reasonable Surfer patent (US 7,716,225, with Jeff Dean and Alexis Battle), the 2004-filed grant that introduces non-uniform link-click probability weighted by per-link features (anchor text, font size, position, surrounding context). The continuations (US 8,117,209 in 65gp pat-45, US 9,305,099 in 2016) extend the same model. The mechanism for differentiated PageRank flow across links on the same page.
• Ashok Popat, Google OCR & Image-Text Indexing Patents (1 patents) — 1 canonical article covering Popat's translation-inspired OCR research (Popat et al., 2009 onward; US 8,675,012 patent family for selective display of OCR'd text). The methodology reframes OCR as statistical machine translation: image features as the source channel, character sequences as the target, joint decoding with channel and language models maximizes transcription quality. Powers Google Books indexing, Lens text capture, Drive PDF search, and the image-bound-text indexing pipeline behind every image and infographic on the web.

Why this organization

Patent law clusters intellectual property by inventor and assignee, not by topic. Grouping by inventor recovers the narrative arc — Amit Singhal's decade of ranking work, Pandu Nayak's BERT-era query handling, Krishna Bharat's news ranking lineage. Each track reads like a research biography written in claim language.