SMXL Milan 2019 Graphs of Things

Bill Slawski
Bill SlawskiDirector of SEO Research at Go Fish Digital
6-7, NOVEMBER 2019
Graphs of Things
Bill Slawski
Director of SEO Research
(GoFishDigital)
@bill_slawskiwww.smxl.it #SMXL19
Our Future is An Internet of
Things
Things that may get smarter and
do away with a need for owner’s
manuals – which should be built
into devices, appliances and
vehicles.
@bill_slawskiwww.smxl.it #SMXL19
Smart Things that are getting
Smarter
I should be able to ask my car
what kind of steering fluid to
use, and it should be able to
answer me.
@bill_slawskiwww.smxl.it #SMXL19
We May Find Answers About
them in Graphs of Things
I did find the right fluid, but
without my car’s help. The
internet of things hasn’t quite
reached all things yet. But the
internet is increasingly about
things.
Graphs of
Things on
my
computer
Google Related Questions now use a Question Graph
Generating related questions for search queries
US Patent: 9,679,027
Granted: June 13, 2017
Filed: December 14, 2015
@bill_slawskiwww.smxl.it #SMXL19
Recommendation: Entity
Oriented Search
This Book is available Open Access,
by Krisztian Balog, a professor of
computer science at the University
of Stavange, and a former intern at
Google. It is very detailed.
https://www.springer.com/gp/book/
9783319939339
@bill_slawskiwww.smxl.it #SMXL19
Or in Augmentation Queries
Query augmentation
US Patent: 9,916,366
Granted: March 13, 2018
Filed: July 28, 2015
@bill_slawskiwww.smxl.it #SMXL19
Augmentation of Brand Queries
with Paid Results
Combining content with a
search result
Assignee: Google LLC
US Patent: 9,947,026
Granted: April 17, 2018
Filed: May 12, 2016
@bill_slawskiwww.smxl.it #SMXL19
Augmentation of Queries with
GMB Location Extensions
Determining Relevant
Business Locations Based
on Travel Distances
Assignee: Google LLC
US Patent Application:
20190180326
Published: June 13, 2019
Filed: February 19, 2019
@bill_slawskiwww.smxl.it #SMXL19
Augmentation of Queries with
Knowledge Graph Information
Providing search results
using augmented search
queries
Assignee: Google LLC
US Patent: 10,055,462
Granted: August 21, 2018
Filed: March 15, 2013
@bill_slawskiwww.smxl.it #SMXL19
New Universal
Search Results
Interface for a universal
search
Inventors: Bret S. Taylor,
Marissa Ann Mayer, Orkut
Buyukkokten
Assignee: Google LLC
US Patent: 10,409,865
Granted: September 10,
2019
Filed: April 15, 2016
@bill_slawskiwww.smxl.it #SMXL19
Recommendation: Paul Haahr in
How Google Works
How Google Works: A Google
Ranking Engineers Story -
https://youtu.be/iJPu4vHETXw
Talks about “Life of a Query” class at Google with “Query Understanding,” asking
About Named Entities in Queries
@bill_slawskiwww.smxl.it #SMXL19
Recommendation: -Jason
Barnard’s Interview of Gary Illyes
How Google Search Ranking Works – Darwinism in Search -
https://www.searchenginejournal.com/how-google-search-ranking-works/307591/
Gary Talks about what is taught in a class for new Google Search engineers, and
how queries work and pages are ranked. Again, Entities are one of the features
that is ranked
@bill_slawskiwww.smxl.it #SMXL19
Recommended Viewing:
Introducing the Knowledge graph
.
Introducing the Knowledge Graph -
https://www.youtube.com/watch?v=mmQl6VGvX-c
@bill_slawskiwww.smxl.it #SMXL19
Knowledge Panels for Things in
the Knowledge Graph
Can Enter Google’s Knowledge Graph by GMB
Verification
https://support.google.com/business/answer/71072
42?hl=en
or by meeting Notability requirements of Wikipedia
https://en.wikipedia.org/wiki/Wikipedia:Notability
Create a Wikidata Entry for your entity
https://www.wikidata.org/wiki/Wikidata:Contribute
Use Schema Markup on your Website
https://schema.org/
@bill_slawskiwww.smxl.it #SMXL19
Knowledge Graph is Powered by
Knowledge Bases
Wikipedia
IMDB
Wikidata
Freebase
Recommended Reading: From Freebase to
Wikidata: The Great Migration -
https://static.googleusercontent.com/medi
a/research.google.com/en//pubs/archive/4
4818.pdf
@bill_slawskiwww.smxl.it #SMXL19
A Knowledge Graph is Made of
Triples
Subject/Verb/Object
Planet of the Apes Rated G
Planet of the Apes Released 1968
Planet of the Apes Directed by
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
@bill_slawskiwww.smxl.it #SMXL19
Triples can come from Tables
Knowledge Bases Often Contain
Facts about Properties of Entities
In table form
Learning objects and facts from
documents
Invented by Shubin Zhao
Assigned to Google
US Patent 8,812,435
Granted August 19, 2014
Filed November 16, 2007
@bill_slawskiwww.smxl.it #SMXL19
Recommended Reading
10 Years of Web
Tables
https://web.eecs.umi
ch.edu/~michjc/paper
s/p2140-cafarella.pdf
@bill_slawskiwww.smxl.it #SMXL19
Triples come from Schema
A Knowledge Graph Can
Learn
Facts from Schema on Web
Pages
<script type="application/ld+json">
{ "@context" : "http://schema.org/",
"@type" : "Person",
"name" : "Bill Slawski",
"url" : "http://www.seobythesea.com/",
"sameAs" : [
"https://twitter.com/bill_slawski",
"https://www.facebook.com/bill.slawski",
"http://instagram.com/billslawski/",
]
}
</script></p>
@bill_slawskiwww.smxl.it #SMXL19
Triples come from Unstructured
Content
Data
@bill_slawskiwww.smxl.it #SMXL19
Google Extracts Entities and
Facts
Computerized systems and
methods for extracting and
storing information regarding
entities
Assignee: GOOGLE LLC
US Patent: 10,198,491
Granted: February 5, 2019
Filed: July 6, 2015
@bill_slawskiwww.smxl.it #SMXL19
Google May Give Scores for
Properties and Types
@bill_slawskiwww.smxl.it #SMXL19
Association Scores Have Different
WeightsAssociation scores 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)
@bill_slawskiwww.smxl.it #SMXL19
Entity Graph
Reconciliation
Automatic discovery of new
entities using graph reconciliation
Inventors: Oksana Yakhnenko and
Norases Vesdapunt
Assignee: GOOGLE LLC
US Patent: 10,331,706
Granted: June 25, 2019
Filed: October 4, 2017
@bill_slawskiwww.smxl.it #SMXL19
Entity Relationship Model
Information extraction from question and answer websites
US Patent: 10,452,694
Granted: October 22, 2019
Filed: December 20, 2017
@bill_slawskiwww.smxl.it #SMXL19
Entity Relationship Scores
1. Visit Q&A sites (like Quora, Yahoo
Answers)
2. Identify Entity in Question Using NLP
3. Identify Candidate Entities in Answer Using NLP
4. Identify Relationship type from the question
5. Score the relationship of Question and Answer
Entities by things such as how frequently the Answer
appears for that question
“WHO/pronoun IS/verb BARACK OBAMA/noun
MARRIED/adjective TO/verb?”
MICHELLE OBAMA/noun.”
Recommended Reading
• Natural Language Processing is Fun! -
https://medium.com/@ageitgey/natural-
language-processing-is-fun-9a0bff37854e
@bill_slawskiwww.smxl.it #SMXL19
Question-Answering by Building
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
@bill_slawskiwww.smxl.it #SMXL19
Thank you/Questions
Bill Slawski
Author at SEObythesea
Director of SEO Research: Go Fish
Digital
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SMXL Milan 2019 Graphs of Things