Entity-Based Search – What is it? What are entities? Where do they come from? And how does Google use them? This presentation answers questions about the history of Google, structured data, the Knowledge Graph, how Rank Brain ties into it and what SEOs need to know about it all.

1. #SearchLeeds @schachin Kristine Schachinger
Data, Data, Everywhere.
Kristine@SitesWithoutWalls.com

2. #SearchLeeds @schachin Kristine Schachinger
In the beginning, there was a …
Large-Scale Hypertextual Web Search Engine

3. #SearchLeeds @schachin Kristine Schachinger
What?

4. #SearchLeeds @schachin Kristine Schachinger
What?

5. #SearchLeeds @schachin Kristine Schachinger
Link Profiles
http://infolab.stanford.edu/pub/papers/google.pdf

6. #SearchLeeds @schachin Kristine Schachinger
The Web 1998

7. #SearchLeeds @schachin Kristine Schachinger
Google Goes To Work
http://infolab.stanford.edu/pub/papers/google.pdf

8. #SearchLeeds @schachin Kristine Schachinger
In 2018 …
Roughly half of the world's population or
3.8 billion people use the internet every day.

9. #SearchLeeds @schachin Kristine Schachinger
Google processes
TRILLIONS of queries a year
& has indexed BILLIONS of Websites.

10. #SearchLeeds @schachin Kristine Schachinger
IN 2015, THERE WERE
2,834,650,000,000 Google searches with
an average 7,766,000,000 searches a day.

11. #SearchLeeds @schachin Kristine Schachinger
Breaks down to …
5.5 billion searches per day
or over 63,000 search queries per second.

12. #SearchLeeds @schachin Kristine Schachinger
That is a lot of data.
#DIDYOUNEEDASLIDEFORTHIS?

13. #SearchLeeds @schachin Kristine Schachinger
Dealing With Data.

14. #SearchLeeds @schachin Kristine Schachinger

15. #SearchLeeds @schachin Kristine Schachinger
Google was founded on unstructured data.

16. #SearchLeeds @schachin Kristine Schachinger
Unstructured data (or unstructured information) is information that
either does not have a pre-defined data model or is not organized in a
pre-defined manner. Unstructured information is typically text-heavy,
but may contain data such as dates, numbers, and facts as well.
https://www.google.co.uk/search?q=definition+unstructured+data&oq=definition+unstructured+data&aqs=chrome..69i57j0l5.5175j0j7&sourceid=chrome&ie=UTF-8

17. #SearchLeeds @schachin Kristine Schachinger
Unstructured Data
uses keywords.
https://moz.com/blog/7-advanced-seo-concepts

18. #SearchLeeds @schachin Kristine Schachinger
TF-IDF
Term Frequency Inverse
Document Frequency
ie the frequency of keywords
https://moz.com/blog/7-advanced-seo-concepts

19. #SearchLeeds @schachin Kristine Schachinger
As queries number in the trillions
unstructured data becomes inefficient.
Data needs structure.

20. #SearchLeeds @schachin Kristine Schachinger
So Google moved from
Relational Databases to
Knowledge Graphs.
Knowledge Graphs

21. #SearchLeeds @schachin Kristine Schachinger
NOTE
Knowledge Graphs
DO NOT EQUAL
THE KNOWLEDGE GRAPH
Knowledge Graphs

22. #SearchLeeds @schachin Kristine Schachinger
Graph-based knowledge representation has been researched for
decades and the term knowledge graph does not constitute a new
technology. Rather, it is a buzzword reinvented by Google and
adopted by other companies and academia to describe different knowledge
representation applications.
Knowledge Graphs
http://ceur-ws.org/Vol-1695/paper4.pdf

23. #SearchLeeds @schachin Kristine Schachinger
Enter Semantic Search
https://web.archive.org/web/20090516213508/http://blog.searchenginewatch.com/090512-201139

24. #SearchLeeds @schachin Kristine Schachinger
https://web.archive.org/web/20090516213508/http://blog.searchenginewatch.com/090512-201139
What is Semantic Search?

25. #SearchLeeds @schachin Kristine Schachinger
Semantic Search
=
Understanding Intent

26. #SearchLeeds @schachin Kristine Schachinger
Welcome G Squared

27. #SearchLeeds @schachin Kristine Schachinger
Google Squared
Google Squared returns search results in a spreadsheet format. It
structures the unstructured data on web pages. So a search for Small
Dogs returns results with names, description, size, weight, origin,
etc., in columns and rows.
Google is looking for data structures on the web that imply facts, and
then grabbing it for Squared results. “It takes an incredible amount of
compute power to create one of those squares,” she says.”
~Techcrunch
https://techcrunch.com/2009/05/12/what-is-google-squared-it-is-how-google-will-crush-wolfram-alpha-exclusive-video/

28. #SearchLeeds @schachin Kristine Schachinger
https://searchengineland.com/up-close-google-squared-19313
Before the Knowledge Graph

29. #SearchLeeds @schachin Kristine Schachinger
https://searchengineland.com/up-close-google-squared-19313
Before the Knowledge Graph

30. #SearchLeeds @schachin Kristine Schachinger
Google Squared
“Check out this example below, a Square for the search “dog breeds.” It’s cool that you can
add major or minor medical concerns to the list of columns, but the selection of examples is
really strange.
Call it structured data if you like,
I call it a surefire recipe for making a bad dog buying decision.”
https://readwrite.com/2009/06/03/google_squared_is_live_who_knew_structured_data_co/

31. #SearchLeeds @schachin Kristine Schachinger
Google Kills Google Squared.
RIP Google Squared 2009-2011

32. #SearchLeeds @schachin Kristine Schachinger
”…quite possibly ...
one of Google's significant achievements”
Nathania Johnson of Search Engine Watch
https://web.archive.org/web/20090516213508/http://blog.searchenginewatch.com/090512-201139
Knowledge Graphs

33. #SearchLeeds @schachin Kristine Schachinger
Why?

34. #SearchLeeds @schachin Kristine Schachinger
https://searchengineland.com/up-close-google-squared-19313
“Strings to Things"
The Holy Grail of Search?
NLP (Natural Language Processing).

35. #SearchLeeds @schachin Kristine Schachinger
But Google doesn’t process
Natural Language.
“Strings to Things"

36. #SearchLeeds @schachin Kristine Schachinger
However, this was the early stages of Google
moving search from strings (unstructured data)
or the “bag of words” approach
 to “things” (structured data).
“Strings to Things"

37. #SearchLeeds @schachin Kristine Schachinger
“Things” are known objects
with known (or learned) relationships.
“Strings to Things"

38. #SearchLeeds @schachin Kristine Schachinger
https://searchengineland.com/up-close-google-squared-19313
Before THE Knowledge Graph – Wonder Wheel

39. #SearchLeeds @schachin Kristine Schachinger
https://searchengineland.com/up-close-google-squared-19313
Before the Knowledge Graph – Wonder Wheel

40. #SearchLeeds @schachin Kristine Schachinger
Welcome THE Knowledge Graph 2012.

41. #SearchLeeds @schachin Kristine Schachinger

42. #SearchLeeds @schachin Kristine Schachinger
Knowledge Graphs are based on known relationships.
THE Knowledge Graph is Google’s graph database.
THE Knowledge Graph

43. #SearchLeeds @schachin Kristine Schachinger
The Knowledge Graph (Google) is seeded by things known.
Instead of just text without meaning, The KG is a relational
graph with known objects and mapped relationships.
THE Knowledge Graph

44. #SearchLeeds @schachin Kristine Schachinger
"Four years ago this July, Google acquired Metaweb,
bringing Freebase and linked open data to Google," he wrote.
Google software engineer Barak Michener
http://www.eweek.com/database/google-releases-cayley-open-source-graph-database
THE Knowledge Graph Seeds

45. #SearchLeeds @schachin Kristine Schachinger
Also includes trusted sources such as the
CIA Fact Book, Wikipedia, Wikidata etc.
http://www.eweek.com/database/google-releases-cayley-open-source-graph-database
THE Knowledge Graph Seeds

46. #SearchLeeds @schachin Kristine Schachinger
Why the Knowledge Graph?
To help better match user intent.
THE Knowledge Graph

47. #SearchLeeds @schachin Kristine Schachinger
The Knowledge Graph enables you to search for things, people or places
that Google knows about—landmarks, celebrities, cities, sports teams,
buildings, geographical features, movies, celestial objects, works of art
and more—and instantly get information that’s relevant to your query
THE Knowledge Graph

48. #SearchLeeds @schachin Kristine Schachinger
In other words
NOUNS
THE Knowledge Graph

49. #SearchLeeds @schachin Kristine Schachinger
NOUNS=ENTITIES
THE Knowledge Graph

50. #SearchLeeds @schachin Kristine Schachinger
Google moves to
ENTITY SEARCH
THE Knowledge Graph

51. #SearchLeeds @schachin Kristine Schachinger
Knowledge Graph entities
The Knowledge Graph has millions of entries that describe real-world entities like people, places, and things. These
entities form the nodes of the graph.
The following are some of the types of entities found in the Knowledge Graph:
Book
BookSeries
EducationalOrganization
Event
GovernmentOrganization
LocalBusiness
Movie
MovieSeries
MusicAlbum
MusicGroup
MusicRecording
Organization
Periodical
Person
Place
SportsTeam
TVEpisode
TVSeries
VideoGame
VideoGameSeries
WebSite

52. #SearchLeeds @schachin Kristine Schachinger
Entities + Relationships=
Knowledge Graph
THE Knowledge Graph

53. #SearchLeeds @schachin Kristine Schachinger
Knowledge Graph
= the Answer Engine
THE Knowledge Graph

54. #SearchLeeds @schachin Kristine Schachinger
Knowledge Graph
= the Answer Engine
THE Knowledge Graph

55. #SearchLeeds @schachin Kristine Schachinger
Google as an Answer Engine
https://www.google.com/search/howsearchworks/responses/#?modal_active=none

56. #SearchLeeds @schachin Kristine Schachinger
Hummingbird  “Strings to Things”.

57. #SearchLeeds @schachin Kristine Schachinger

58. #SearchLeeds @schachin Kristine Schachinger
Hummingbird
The name was derived from
the speed and accuracy of the hummingbird.
“Strings to Things"

59. #SearchLeeds @schachin Kristine Schachinger
Hummingbird Arrives 2013
Google moves from matching keyword terms to
Google trying to process Natural Language Queries.
“Strings to Things"

60. #SearchLeeds @schachin Kristine Schachinger
But Google doesn’t process
Natural Language.
“Strings to Things"

61. #SearchLeeds @schachin Kristine Schachinger
Hummingbird adds a semantic layer to the search
algorithms utilizing structured data.
“Strings to Things"

62. #SearchLeeds @schachin Kristine Schachinger
Hummingbird adds a
semantic layer to the
search algorithms like
synonyms and close
variants.
https://moz.com/blog/7-advanced-seo-concepts

63. #SearchLeeds @schachin Kristine Schachinger
Hummingbird adds a
semantic layer to the
search algorithms that
uses “semantic distance
and term relationships”.
https://moz.com/blog/7-advanced-seo-concepts

64. #SearchLeeds @schachin Kristine Schachinger
Hummingbird adds a
semantic layer to the
search algorithms that
uses “phrase based
Indexing and co-
occurrence.”
https://moz.com/blog/7-advanced-seo-concepts

65. #SearchLeeds @schachin Kristine Schachinger
Page Segmentation.
This part of the
algorithm determines
meaning through
placement.
https://moz.com/blog/7-advanced-seo-concepts

66. #SearchLeeds @schachin Kristine Schachinger
Entity Salience.
This part of the
algorithm determines
meaning through known
relationships.
https://moz.com/blog/7-advanced-seo-concepts

67. #SearchLeeds @schachin Kristine Schachinger
Google doesn’t process
Natural Language.
This means we must add an “interpreter”.

68. #SearchLeeds @schachin Kristine Schachinger
Enter Structured Data & Schema
https://web.archive.org/web/20090516213508/http://blog.searchenginewatch.com/090512-201139

69. #SearchLeeds @schachin Kristine Schachinger
What is Structured Data?

70. #SearchLeeds @schachin Kristine Schachinger
What is Structured Data?
Structured data for SEO purposes is on-page markup that
enables search engines to better understand the information
currently on your site’s web pages, and then use this information
to improve search results listing by better matching user intent.

71. #SearchLeeds @schachin Kristine Schachinger
What is Structured Data?
This structured data is defined by using schema to act as the
interpreter. This is the definition we add to the page using
schema code.
Google allows 3 types.
• RDFa
• Microdata
• JSON-LD

72. #SearchLeeds @schachin Kristine Schachinger
Schema
JSON-LD is the recommended schema code.
JSON-LD stands for JavaScript Object Notation for Linked Data
This is just a way to implement schema outside the HTML mark-up
structure. RDFa and Microformats required the code to be implemented
via HTML.

73. #SearchLeeds @schachin Kristine Schachinger
Schema
Benefit is it can be removed from the HTML structure, which
makes it easier to write, implement, and maintain.
For a good breakdown on what JSON is at the code level.
Portent’s JSON Implementation Guide is very helpful.
https://www.portent.com/blog/seo/json-ld-implementation-guide.htm

74. #SearchLeeds @schachin Kristine Schachinger
JSON-LD Schema

75. #SearchLeeds @schachin Kristine Schachinger
Schema
IMPORTANT! Test your JSON-LD.
Use the Google Structured Mark-Up Helper.
https://search.google.com/structured-data/testing-tool

76. #SearchLeeds @schachin Kristine Schachinger
Schema
NOTE this tool only tells you if it is semantically correct, NOT if
you are using the proper schema.
Make sure to check with Google’s Guides on schema
implementation. Improper use or implementation can result in
a manual action.
• https://developers.google.com/search/docs/guides/intro-structured-data
• https://developers.google.com/search/docs/guides/prototype

77. #SearchLeeds @schachin Kristine Schachinger
Schema
IMPORTANT! Your JSON content MUST match what is in the
page exactly. If they differ, you will likely get a manual action as
Google sees this as cloaking.

78. #SearchLeeds @schachin Kristine Schachinger
Schema

79. #SearchLeeds @schachin Kristine Schachinger
Ranking Without Links

80. #SearchLeeds @schachin Kristine Schachinger
Rank Brain

81. #SearchLeeds @schachin Kristine Schachinger
Rank Brain is used for Unknown Queries where entity
meanings/relationships are unclear or unknown.

82. #SearchLeeds @schachin Kristine Schachinger
Rank Brain.
Only algorithm that uses AI
on the live results
Rank Brain.

83. #SearchLeeds @schachin Kristine Schachinger
Rank Brain

84. #SearchLeeds @schachin Kristine Schachinger

85. #SearchLeeds @schachin Kristine Schachinger
Presence of Rank Brain means
Google is confused …

86. #SearchLeeds @schachin Kristine Schachinger
Why?
Google does not use NLP
(Natural Language Processing)
Rank Brain.

87. #SearchLeeds @schachin Kristine Schachinger
Uses Structured Data, Entities & Known Relationships
Person, Place, Thing = Noun = Entities.
Nouns or Persons/Places/People/Things are what we call entities. Entities are
known to Google and their meaning is defined in the databases Google references.
Rank Brain.

88. #SearchLeeds @schachin Kristine Schachinger
Rank Brain Also Uses Users Queries & Clicks
to Help It Understand Query Intent.

89. #SearchLeeds @schachin Kristine Schachinger
Should you optimize for it?
Rank Brain.

90. #SearchLeeds @schachin Kristine Schachinger
Why would you optimize to rank with AI?
Rank Brain.

91. #SearchLeeds @schachin Kristine Schachinger
(Gary Illyes)
Rank Brain.

92. #SearchLeeds @schachin Kristine Schachinger
Just write in natural and conversational language.

93. #SearchLeeds @schachin Kristine Schachinger
So why do we care about this?

94. #SearchLeeds @schachin Kristine Schachinger
We can act as the interpreter and help “teach”
Google what our site is about.

95. #SearchLeeds @schachin Kristine Schachinger
Adding semantic mark-up
(structured data via schema) allows us to tell
Google what WE SAY our site is about and WHAT
RELATIONSHIPS we define within it.

96. #SearchLeeds @schachin Kristine Schachinger
We can act as the interpreter and help “teach”
Google the context of our content.

97. #SearchLeeds @schachin Kristine Schachinger

98. #SearchLeeds @schachin Kristine Schachinger
We can help give Google a clearer understanding.
And in the end that helps us help Google better
answer the questions users ask and to better
surface our content where we want it.
We give our data meaning Google understands.

99. #SearchLeeds @schachin Kristine Schachinger

100. #SearchLeeds @schachin Kristine Schachinger
Data, Data, Everywhere.
Kristine@SitesWithoutWalls.com