Yossi Matias, Google SERP Features & Assistant Patents | Google Patents

By NizamUdDeen · Updated January 1, 2026 · Reviewed by the Nizam SEO War Room editorial team.

First, the short version. Below is the AIO-eligible passage and the question-format primer for Yossi Matias, Google SERP Features & Assistant 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.

About the Yossi Matias, Google SERP Features & Assistant Patents track

People-Also-Ask & Query Surfaces

Generating Related Questions for Search Queries (US 9,213,748 · December 15, 2015)
Generating Related Questions for Search Queries (2017) (US 9,679,027 · June 13, 2017)
Generating Additional Content (US App 2016/0026727 · January 28, 2016)
Query Formulation and Search in the Context of a Displayed Document (US 9,342,601 · May 17, 2016)
Third Party Search Applications for a Search System (US 10,289,618 · May 14, 2019)

Entity-Driven SERP Features

Identifying Central Entities (US 9,009,192 · April 14, 2015)
Grouping Related Entities (US 9,411,857 · August 9, 2016)
Providing an Explanation of a Missing Fact Estimate (US 10,318,540 · June 11, 2019)
Selecting Textual Representations for Entity Attribute Values (US 10,685,073 · June 16, 2020)
Searching Quotes of Entities Using a Database (US 10,198,508 · February 5, 2019)

Trends, Analytics & Ads

Campaign and Competitive Analysis and Data Visualization Based on Search and Social Media (US 9,043,302 · May 26, 2015)
Ranking Graphical Visualizations of a Data Set According to Data Attributes (US 8,812,947 · August 19, 2014)
Advertising Inventory Allocation (US 8,615,436 · December 24, 2013)

Assistant, Duplex & Modern AI

Automated Call Requests with Status Updates (US 10,827,064 · November 3, 2020)
Automated Call Requests with Status Updates (app 2019) (US App 2019/0306314 · October 3, 2019)
Automated Call Requests (app 2024) (US App 2024/0187521 · June 6, 2024)
Reducing Telephone Network Traffic Through Pre-Call Information (US App 2024/0205331 · June 20, 2024)
Synchronous Communication Using Voice and Text (US 11,811,968 · November 7, 2023)
Synchronous Communication Using Voice and Text (2025) (US 12,301,754 · May 13, 2025)
System(s) and Method(s) for Implementing a Personalized Chatbot (US 12,225,158 · February 11, 2025)
Personalized Chatbot (app 2025) (US App 2025/0150532 · May 8, 2025)
Large Language Model Output Entailment (US App 2025/0094456 · March 20, 2025)
Generating a Composite Response to Natural Language Input (US App 2025/0069597 · February 27, 2025)
Selectively Generating Expanded Responses That Guide Continuance of a Human-to-Computer Dialog (US App 2022/0157308 · May 19, 2022)
Audio-Visual Hearing Aid (US App 2024/0428816 · December 26, 2024)
Audio-Visual Hearing Aid (app 2023) (US App 2023/0267942 · August 24, 2023)
Using Video Clips as Dictionary Usage Examples (US App 2025/0173509 · May 29, 2025)
Text-to-Speech Interface Featuring Visual Content Supplemental to Audio Playback (WO2020023070A1 · January 30, 2020)
Aggregation of Related Media Content (US 11,335,380 · May 17, 2022)
Aggregation of Related Media Content (2020) (US 10,770,112 · September 8, 2020)
Automatic Execution of Actions by a Mobile Computing Device (DE112019000305T5 · November 5, 2020)
Dynamically Updating User Interface Elements (EP3827332A1 · June 2, 2021)

ML Models & Generative Editing

Neural Networks with Selective Attention Layers (WO2026044251A1 · February 26, 2026)
Text-Driven Image Editing via Image-Specific Finetuning of Diffusion Models (EP4581581A1 · July 9, 2025)
Text-Driven Image Editing (WO) (WO2024086598A1 · April 25, 2024)
Conditioning Text-to-Image Generative Neural Networks (WO2024249439A1 · December 5, 2024)
Video Editing Using Diffusion Models (WO2024163624A1 · August 8, 2024)
Methods and Systems for Fast Inference from Machine Learning Models (WO2024118603A1 · June 6, 2024)
Partially Customized Machine Learning Models for Data De-identification (US App 2021/0303725 · September 30, 2021)

Social, Contacts & Other Infrastructure

Generating Contact Suggestions (US 9,934,286 · April 3, 2018)
Generating Contact Suggestions (2016) (US 9,311,415 · April 12, 2016)
Systems and Methods for Providing Contact Group Member Suggestions (US 9,773,229 · September 26, 2017)
Generating Suggestions for User Groups in Social Networks (US 8,977,649 · March 10, 2015)
Generating Suggestions for User Groups (2014) (US 8,880,607 · November 4, 2014)
Security for Wireless Broadcasts (US 10,616,765 · April 7, 2020)
Security for Wireless Broadcasts (EP) (EP3320711A1 · May 16, 2018)
Panoramic Video Acquisition Guidance (US App 2015/0124047 · May 7, 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.

For example, a working SEO consultant uses Yossi Matias, Google SERP Features & Assistant Patents when diagnosing a ranking drop, planning a content calendar, or briefing a client on why a tactic shifted. However, the concept only compounds when paired with the surrounding entries in the encyclopedia and patents archive. In addition, the platform connects this concept to live SERP data so the theory carries through to execution.

Finally, to summarize. Yossi Matias, Google SERP Features & Assistant Patents matters because it intersects directly with the signals search engines and AI answer engines use to rank and surface results. The full article above covers the mechanism in depth, the patents it derives from, and the related encyclopedia entries to read next.