Knowledge Graph Explained

1
The Knowledge Graph.
What is it?
How Does it work?
How do you get in?
Jason Barnard
@jasonmbarnard
jasonbarnard
jasonbarnard
kalicube.pro

2Watch the series: Kalicube.pro/ws3
#SEOisAEO
Thanks and Kudos :)

3#SEOisAEO - The Knowledge Graph jasonmbarnardYoastCon 2019 jasonbarnard
AEO
1. Answer
2. Assistive
3. Awesome
Engine Optimisation
Engine Optimisation
Engine Optimisation

1. Graph Theory

1. Graph Theory
2. What are Knowledge Graphs

1. Graph Theory
3. How Knowledge Graphs are being Built

1. Graph Theory
4. Who Else is Playing the Game

1. Graph Theory
5. How to get into these Knowledge Graphs

1. Graph Theory
2. Knowledge Graphs
5. How to get into these Knowledge Graphs
6. A Rather Groovy Example
(We all know and love)

What do all these
have in common?

Graph theory
Nodes, attributes and edges

Vaidehi Joshi @vaidehijoshi

Weighting
6 yrs
4 yrs
8 yrs
1 yr
3 yrs
10 yrs
2 yrs
3 yrs

A knowledge graph
Entities with types, properties and relationships

Jo Stichbury @fluffymaccoy
Knowledge graphs are large networks of
entities, their semantic types, properties, and
relationships between those entities”
M Kroestch and G Weikum

Kate knows Mary.
Mary likes Pete.
Mary age "32".
Pete brother_of Kate.
Pete born_on "27-03-1982".

S
to
Things

Knowledge graphs =
the hub of Answer Engines

A
Q
Relevancy
Understanding
Credibility

Building a Knowledge Graph

2005 - the Fact Repository

In general, knowledge graphs can be created by
1. manual curation
2. crowdsourcing
3. ...

A combination of :
1. manual curation
2. crowdsourcing
3. (semi-) automatic extraction

Xin Luna Dong - my new favourite person :)

Xin Luna Dong - my new favourite person :)
Research on knowledge management,
data cleaning and integration,
information extraction, graph mining and
embedding, knowledge-based search…

Head knowledge mainly collected by manual curation or importing large datasets
How to collect long tail knowledge in a scalable way?
Xin Luna
Dong

The web as a database:
The biggest knowledge graph ever
Imagine you could get the entire web in a database, and structure it. Then you would be able to get
answers to complex questions in seconds by querying, rather than searching.
This is what Diffbot promises.

Xin Luna
Dong

Annotated Web
Schema / Structured Data

Tables and lists
Seemingly simple
Devilishly tricky, apparently

DOM extraction
Yelp, Amazon and other sites with solid HTML
providing semi-structured data

Free Texts
NLP, relatedness and co-occurence, topical siloing,
semantic triples...

It is one thing extracting the data
and making (some) sense of it

But is it true?

But is it true?
TRUST based Knowledge

Manually curated
Xin Luna
Dong
Extracted

Breaking News
Associate scores / confidence

Node "Bryce Harper" 201 with
attribute has_birthday
date entity node "Oct. 16, 1992" 203
association score of 0.84

Node "Bryce Harper" 201 with
attribute has_career_HR_total
value entity node "60 Home Runs" 204
association score of 0.37

The difference in these association scores
(confidence) may arise due to

- the reliability of the sources used to
generate such relationships

generate such relationships
- the frequency of co-occurrences between
the entities

generate such relationships,
the entities
- the fact that one of the attributes values
(node 204) is changing over time

generate such relationships,
the entities
- the fact that one of the attributes values
(node 204) is changing over time
- and/or other factors

Who is playing the game ?
(and how well)

There are 1224 datasets in the
Linked Open Data Cloud

Containing over 40 billion facts

How you can get into these
Knowledge Graphs

Communicate

Communicate
Corroborate

1. Who you are
Communicate
Corroborate

1. Who you are
2. What you offer
Communicate
Corroborate

1. Who you are
2. What you offer
3. In detail
Communicate
Corroborate

*Typical* Steps to the Knowledge Graph
1. Use Structured Data on your site
2. Quality About Us page
3. Get a Wikipedia Page
4. Add yourself to Wikidata
5. Have a Google My Business
6. Confirmation from Trusted Sources
7. ...

Confirmation
20
to
30

Where to start

Find your
springboard
Boinggggg!!!!

Noteworthy + Proof = Deeper Understanding

A working example

Knowledge graphs ...
Suitable for a continuous flow of large amounts of data from
diverse, heterogenous sources.
The ontology (semantics of the data) can be extended and
revised algorithmically as new data arrives.
Jo Stichbury @fluffymaccoy
(paraphrased)

“Google Maps is a great example of what the
future of search should look like — augmented
public data, powered by a knowledge graph.
Ivan Bercovich (Graphiq - now Alexa)

Ivan Bercovich (Graphiq - now Alexa)
Google is able to maintain a
real-time representation of the world
and answer geospatial queries
that have never been asked.

Conclusion

A
Q
Relevancy
Understanding
Credibility

86
The Knowledge Graph
Thanks !
Jason Barnard
@jasonmbarnard
jasonbarnard
jasonbarnard
kalicube.pro

Knowledge Graph Explained

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