BrightonSEO March 2021 | Dan Taylor, Image Entity Tags

Using Image Category Labels
For Content Optimization
Dan Taylor // SALT.agency

Head of Research & Development @ SALT.agency
• 2018 TechSEO Boost Innovation Award
• Search Engine Journal Author
• Search Engine Journal Top 140 (“18, “19, “20)
• SEMrush Top Author
• https://salt.agency (#Hiring #RemoteUK)
• https://hreflangchecker.com
• https://sloth.cloud
• https://dantaylor.online
These slides: https://dantaylor.online/brighton2021
dantaylor.online // @taylordanrw

Today
Today, I’ll be talking about how we can use Google’s imaging labels and
entity classification systems as a method of keyword and topic research,
to improve our content.
“Improve our content”
Rankings? Conversion? User Happiness & Experience Forecasting?
Enhanced topic research to identify/reaffirm connections between
topics we’re exploring. But first, a little back story...
3

Semantic Search & SEO
Semantics in SEO isn’t a new concept, or new to Google.
The first mention of Semantic search came in a 1999 Sergey Brin patent.
If you’re able to understand entities, then you can gain an insight into
how Google looks at individual webpages, websites (as a cohort of
pages), and then interprets the information contained therein.
Topic clusters have nothing to do with Hummingbird, and RankBrain.
#Myth
4

“
So, when someone searches. Google may compare
the SERPs they receive from the original query
to augmented query results based on previous
searches using the same query terms or
synthetic queries. This evaluation against
augmentation queries is based upon which search
results have received more clicks in the past. Google
may decide to add results from an
augmentation query to the results for the query
searched for to improve quality scores and the
overall search results.
5
Bill Slawski

Sphere of influence
As SEOs, we can only impact the initial phase, and our efforts are
then see as rewards during the indexing and ranking phases.
6

What is an image entity
tag/category label?

“
Per some embodiments, object
recognition technology is used to
annotate images stored in
databases or harvested from
Internet web pages. The annotations
may identify who and/or what is
contained in the images.
9
US Patent: 10,534,810 - Ran El Manor and Yaniv Leviathan, Google LLC

Images & The Knowledge Graph
Back in 2012, when Google started the Knowledge Graph they included a
phrase that “(Google) can learn from images of real-world objects”
We know from other patents that Google annotates images as part of
the mechanisms to grow and increase connections within the
Knowledge Graph between entities (object and attribute).
It’s logical that this would be a two way process; with learnings from
image attribute entity recognition feeding into the overall knowledge
sphere, and vice versa.
10

Chuck Rosenberg, Image Search Team - 2013
11

5 Query Satisfaction Objectives
1. Continuation of neural mapping processes to provide better results
for ambiguous queries
2. Improve needs met results for queries with multiple common
(strong) interpretations
3. Advancement beyond the “written word” in terms of entity
relationship understanding
4. Improve the results (in terms of relevancy) for general image search
5. [Internal] work by Google to test and train against new queries/tests
to perform updates/reaffirm data sets/improve data sets/entity
relationships
12

Scores
We know from patent analysis (hail Bill Slawski) that Google uses
association scores (the score to quantify the relationship between two
entities within a database).
We know that Google then has entity classes, and subclasses. Entities
may be associated with one or more entity attributes and/or object
attributes.
This then begs the question of how association and confidence scores
and impact the tangible output (the image filter tags).
13

“
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. In some embodiments,
for example, an association score may reflect a
degree of relatedness between two entities or a
context and an entity.
14
US Patent 10,198,491, a lot of authors, Google LLC

Illustration from the patent 10,534,810
15

Mapping Entity Relations
From the bear example in the patent we can begin to map out a
relationship between various entities.
How we define or connect the relationships (for the purpose of
improving our user happiness) is down to our own, logical interpretation
- aka common sense.
Google does this through machine learning, and combing the
information from image annotations with prior knowledge from the
Knowledge Graph.
16

Illustration from the patent 10,534,810
17
Node
Edge

18

Ok, great. So why/how
can I use this?

Entities & Content Optimization
Remember that Google is a machine.
When a web crawler looks at an entity, it does so as a node - and then
works to identify relationships between those entities.
They are trained (ML) to look for entities, and identify context and
relationships.
We optimise our internal linking between webpages (that house related
content) like nodes & edges… (IMO) Google can also ascertain relevance
between documents on a single domain, without links - but they help.
22

Scalable Extraction
We can use Python to extract the tags from Google
image search - meaning we can scale this process.
With simple extraction around a small, initial set of
search queries we can begin to identify and
unearth potential relationships between concepts
and entities (various classes) that aren’t
demonstrated in traditional keyword research tools
working off queries alone.
Google likes to update it’s HTML, so you will need to
keep updating your scrapers...
23

[Cyprus Holidays]
24
BEACH
BEACH

[Cyprus Holidays] Image Tags
● All inclusive
● Ayia Napa
● Cheap
● Protara
● Beach
● 5 Star
● Nissi Beach
● Larnaca
● Coral Bay
● Limassol
25
● Family
● Luxury
● Paphos
● Turkish
● Summer
● Resort
● Waterpark
● Grecian Park
Hotel
● Electra Village
● South
● Anastasia
● Map
● Elysium
● Nestor hotel
● Famagusta
● Pernera
● Night life
Place/Location -- Hotel/Hotel Modifier -- Holiday Modifier

Result #1
holidayhypermarket.co.uk/destinations/cyprus
● All inclusive
● Ayia Napa
● Cheap
● Protara
● Beach
● 5 Star
● Nissi Beach
● Larnaca
● Coral Bay
● Limassol
26
● Family
● Luxury
● Paphos
● Turkish
● Summer
● Resort
● Waterpark
● Grecian Park
Hotel
● Electra Village
● South
● Anastasia
● Map
● Elysium
● Nestor hotel
● Famagusta
● Pernera
● Night life

Result #54
scottdunn.com/cyprus
● All inclusive
● Ayia Napa
● Cheap
● Protara
● Beach
● 5 Star
● Nissi Beach
● Larnaca
● Coral Bay
● Limassol
27
● Family
● Luxury
● Paphos
● Turkish
● Summer
● Resort
● Waterpark
● Grecian Park
Hotel
● Electra Village
● South
● Anastasia
● Map
● Elysium
● Nestor hotel
● Famagusta
● Pernera
● Night life

https://scottmathson.com/blog/2020/04/23/cloudflare-dns-content-hub-case-study-pt-1-seo-rankings/
32

33
Thank you!
@taylordanrw
https://salt.agency

BrightonSEO March 2021 | Dan Taylor, Image Entity Tags

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