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SEO & Patents Vrtualcon v. 3.0

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A look at search-related patents from Google that people who do SEO may be interested in learning about

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SEO & Patents Vrtualcon v. 3.0

  1. 1. SEO & Patents Bill Slawski @bill_slawski
  2. 2. Bill Slawski ● Author at https://www.seobythesea.com ● Director of SEO Research at https://gofishdigital.com ● Twitter: https://twitter.com/bill_slawski ● LinkedIn: https://www.linkedin.com/in/slawski/ ● Jurisdoctor Degree: Widener University School of Law ● SEO since 1996
  3. 3. Why Patents? 1. Protect a Search Engine’s Intellectual Property 2. Exclude other search engines from using technology 3. Not for marketing 4. Related Patents and white papers exist 5. Continuation Patents have updated claims sections. 6. The Purpose Behind Patents are to Spur Innovation.
  4. 4. In Patents Live Algorithms ● Algorithms solve problems ● A patent shows the problems it solves ● Prior history is in the patent ● Patent must be novel, non-obvious, and useful ● A patent must be understandable to someone “learned in the art.” ● Patents show what might be used.
  5. 5. Knowledge in Search Results! Augmented Search Queries Using Knowledge Graph Information Providing search results using augmented search queries Inventors: Emily Moxley and Sean Liu Assignee: Google LLC US Patent: 10,055,462 Granted: August 21, 2018 Filed: March 15, 2013
  6. 6. A Query w/an Entity Shows Knowledge SERPs Rich Snippets Featured Snippets Structured Snippets Carousels Local Pack People Also Ask Questions People Also Search For Related Entities Knowledge Panels
  7. 7. 4th Updated Universal Search has Knowledge Google’s New Universal Search Results Interface for a universal search Inventors: Bret S. Taylor, Marissa Ann Mayer, Orkut Buyukkokten Assignee: Google LLC (Mountain View, CA) US Patent: 10,409,865 Granted: September 10, 2019 Filed: April 15, 2016 From the Version Granted in 2009: 9. The method of claim 1, where the Document categories include at least one of a news category, an image category, or a product category.
  8. 8. Knowledge Graphs (Plural!)
  9. 9. Entity Extraction Entity Extractions for Knowledge Graphs at Google Computerized systems and methods for extracting and storing information regarding entities Inventors: Christopher Semturs, Lode Vandevenne, Danila Sinopalnikov, Alexander Lyashuk, Sebastian Steiger, Henrik Grimm, Nathanael Martin Scharli and David Lecomte Assignee: GOOGLE LLC US Patent: 10,198,491 Granted: February 5, 2019 Filed: July 6, 2015 In web crawling, a node is a page, and an edge is a link between pages; in data crawling, a node is an entity, and an edge is a relationship between entities. It's an evolution in thinking about the web.
  10. 10. A Move Away From Wikipedia Extracting Entities from News and Authoritative sites means less reliance on manually edited Knowledge bases such as Wikipedia or IMDB
  11. 11. Answering Questions Using Knowledge Graphs Answering Questions Using Knowledge Graphs Natural Language Processing With An N-Gram Machine Pub. No.: WO2019083519A1 Publication Date: May 2, 2019 International Filing Date: October 25, 2017 Inventors: Ni Lao, Jiazhong Nie, Fan Yang Business books 2020
  12. 12. Confidence Scores
  13. 13. Entity Rankings from Query Knowledge Graph
  14. 14. Ranked Entities in Search Results Ranked Entities in Search Results at Google Generating ranked lists of entities Inventors: Toshiaki Fujiki, Slaven Bilac, Kavi J. Goel, Shuhei Takahashi, Tomohiko Kimura Assignee: Google LLC US Patent: 10,691,702 Granted: June 23, 2020 Filed: August 31, 2017 Best Science Fiction Books of 2020 Best Houseplants for air quality
  15. 15. More Analysis: Less Knowledge Bases
  16. 16. Quote Search: Knowledge Bases to Videos ● Google Has Updated Quote Searching to Focus on Videos Systems and methods for searching quotes of entities using a database ● Inventors: Eyal Segalis, Gal Chechik, Yossi Matias, Yaniv Leviathan, and Yoav Tzur ● Assignee: Google LLC ● US Patent: 10,198,508 ● Granted: February 5, 2019 ● Filed: June 26, 2017
  17. 17. Claims Updated in Continuation Patent 2017 Version: match the one or more keywords to knowledge graph items associated with candidate subject entities in a knowledge graph stored in one or more databases, 2019 Version performing audio analysis on the audio content to identify a quote in the audio content; determining the user as an author of the audio content based on recognizing the user as the speaker of the audio content; identifying, based on words or phrases extracted from the quote, one or more subject entities associated with the quote;
  18. 18. Google Learning from Images on the Web ● How Google May Annotate Images to Improve Search Results ● Computerized systems and methods for enriching a knowledge base for search queries Inventors: Ran El Manor and Yaniv Leviathan Assignee: Google LLC US Patent: 10,534,810 Granted: January 14, 2020 Filed: February 29, 2016
  19. 19. Bears Hunt Fish in Rivers Main Objects: Bears Secondary Objects: Fish
  20. 20. Semantic Image Categories
  21. 21. Image Search Categories: Entities/Ontologies ● Google Image Search Labels Becoming More Semantic? ● System and method for associating images with semantic entities Inventors: Maks Ovsjanikov, Yuan Li, Hartwig Adam and Charles Joseph Rosenberg; Assignee: Google LLC US Patent: 10,268,703 Granted: April 23, 2019 Filed: December 8, 2016
  22. 22. George Washington Image Categories Catgegories contain Semantically Related Entities which are an ontology, Useful if you want to visually learn about an entity
  23. 23. Website Categories
  24. 24. Classification of Websites ● Google Using Website Representation Vectors to Classify with Expertise and Authority ● Website Representation Vector to Generate Search Results and Classify Website Publication number: WO2020033805 Applicants: GOOGLE LLC Inventors: Yevgen Tsykynovskyy Publication Number WO/2020/033805 Filed: August 10, 2018 Publication Date February 13, 2020
  25. 25. Categories Based on Industry/Expertise Levels ● For instance, the website classifications may include the first category of websites authored by experts in the knowledge domain, e.g., doctors, the second category of websites authored by apprentices in the knowledge domain, e.g., medical students, and a third category of websites authored by laypersons in the knowledge domain.
  26. 26. Queries are Categorized using Query logs, and return results only from the appropriate Category of Website… A Query such as “What are the Symptoms of Diabetes Type 2,” would be answered with An expert medical site run by Doctors. Sites need to meet Thresholds of Quality to Rank for a query. Because the Categories for Queries and for Websites need to match, this Means Google has less pages to sort and rank to respond to a query with, Making it more efficient
  27. 27. Thank you very much! Any Questions? You can always ask later on Twitter: https://twitter.com/bill_slawski I will be sharing these Slides on Slideshare: https://www.slideshare.net/billslawski

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