Google has moved from Search to Knowledge, and Focusing on Answering questions with knowledge graph entity information provides has led to answering queries with Knowledge graphs for those questions, with confidence scores between entities and other entities or attributes of entities, based upon freshness, reliabilillity, popularity, and proximity between an entity and another entity or an attribute.
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
Slawski New Approaches for Structured Data:Evolution of Question Answering
1. #pubcon
Presented by:
Bill Slawski (@bill_slawski)
Director of SEO Research at Go Fish Digital
New approaches for Structured Data:
Evolution of Question-Answering
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But Now This Web - An
Entity Graph
• Tuple = Object/Verb/Subject
• Planet of the Apes Rated G
• Planet of the Apes Released
in 1968
• Planet of the Apes Directed
by Franklin Schaffner
• Planet of the Apes has actor
Roddy McDowall
• Planet of the Apes has actor
Charlton Heston
• Planet of the Apes has actor
Kim Hunter
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Annotations
• Annotations are passed to
requesting objects in
response to queries and are
used to determine search
results. Annotations are also
used to decide whether facts
match and whether facts
contain reasonable values.
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Schema.org –June
2011
• You Can Subscribe to the
Public Schema Mailing List at:
https://lists.w3.org/Archives/P
ublic/public-schemaorg/
• To get involved in discussions
and see information about
monthly updates of schema.org.
It is a good way to keep on top
of one of the fastest growing
areas of SEO
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Rich Results
• The Google Developer pages
detail information about how to
get rich snippets in search
results
https://developers.google.com/
search/reference/overview
• Rich Results are a carrot (reward) for
including Schema Markup on your
pages. Google provides specific
implementation details for the Schema
types listed on the next page.
• They try to influence you to show
richer search results which can help
your content stand out in SERPs, and
earn more clicks.
15. #pubcon@bill_slawski
Types of Rich Results
• Article How-To
Review Snippet
• Breadcrumb Job Posting
Sitelinks Searchbox
• Book Job Training
Software App
• Carousel Livestream
Speakable
• Corporate Contact Local Business Listing Course
Subscription and Paywalled Content
• Critic Review Logo
Video
• Dataset Movie
• Employer Aggregate Rating Occupation
• Event Product
• Fact Check QnA
• FAQ Recipe
16. #pubcon@bill_slawski
Testing Tools
• The Google Structured Data Testing Tool can be
found at: https://search.google.com/structured-
data/testing-tool/u/0/
The Google Rich Results test can be found at:
https://search.google.com/test/rich-results
• Google Search Console reports on:
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Table Data is
Structured Data
• Applying WebTables in
Practice
https://static.googleuserco
ntent.com/media/research
.google.com/en//pubs/arc
hive/43806.pdf
• Ten Years of WebTables
• https://web.eecs.umich.
edu/~michjc/papers/p2140
-cafarella.pdf
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Facts From the Browseable Fact
Repository
• Extracting Facts from Documents
(1) Extract facts, i.e., (subject, attribute,
object) triples, from webpages to
identify values of attributes, i.e.,
“objects” in the extracted triples.
(2) Learn about patterns associated with
those facts and attributes
(3) Score Additional Facts from the
Webpages
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Natural Language
SERPs for Intent
Queries
• 1. Get Intent Questions from Authoritative
Sources
• 2. Get Intent Questions from Query Logs
• 3. Convert Intent Questions into templates:
a. What are the symptoms of XXXXXX
b. What is the Treatment for
XXXXXXXXXX
• 4. Question and Answer Data Store is
collected from authoritative sites
Photo by Johann
Siemens on Unsplash
28. #pubcon@bill_slawski
Interpreting Intent Behind Questions
Evaluating
semantic
interpretations
of a search
query
Granted July
16, 2019
Original ambiguous query: How long is Harry Potter?
Semantic Interpretation: How long is the Book Harry
Potter?
Semantic Interpretation: How long is the movie Harry
Potter?
Semantic Interpretation: How tall is the character
Harry Potter?
Semantic Interpretation: How old is the character
Harry Potter?
Format = Template Question (entity) Image by Kristin Mitchell
29. #pubcon@bill_slawski
The Evolving Knowledge Graph
• Computerized
systems and
methods for
extracting and
storing
information
regarding
entities
Extract Entities, Related Entities and Entity
Classes and Attributes of Entities
Save Information in Tuples:
Object/Verb/Subject
Generate Association Scores between
Entities and Attributes Based upon Factors
30. #pubcon@bill_slawski
Association Scores
• An association score may reflect a likelihood or
degree of confidence that an attribute, attribute
value, relationship, class hierarchy, designated
context class, or other such association is valid,
correct, and/or legitimate.
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Weights Behind
Association Scores
• Association scores
incorporate weights for each
occurrence of an entity or
context.
• temporal weights (recent
documents or occurrences)
• reliability weights (more
reliable sources, more
heavily)
• popularity weights (more
popular sources, more
heavily)
• proximity weights
(entities/contexts occurring
in closer proximity to one
another on a page, more
heavily)
Photo by Victor
Freitas on Unsplash
34. #pubcon@bill_slawski
Question Answering Using Knowledge
GraphsNatural
Language
Processing With
An N-Gram
Machine
Granted
May 2, 2019
1. Use a question as a Query
2. Collect the SERPs from that Query
3. Break Pages from those SERPs into tuples
4. Build a Knowledge Graph From those
tuples
5. Answer the Question
Photo by Roman Kraft on Unsplash
36. #pubcon@bill_slawski
Thank You
• Bill Slawski
• Author at SEObythesea.com
• Director of SEO Research at Go Fish
Digital
• Twitter: @bill_slawski
Photo by Bill Slawski, Cardiff Tidal Pools