Connecting the probable dots in content and data can help significantly and improve your search strategy. Ambiguity in SEO comes in many form too, going beyond content and into entities and locations. This talk touches on some of the areas where ambiguity can impact and hinder your performance

1. Connecting)The)
Probable(Dots
Disambiguating+strategies+for+entity+
oriented(search(and(natural(
language'understanding'
Dawn%Anderson
@dawnieando #FOS20

2. The$probability$
of#rolling#an#even#
number'or'an'
odd#number#is#
1:2

3. This%is%‘Equiprobability’%!
Both%odds$and$evens$are$
equiprobable+outcomes

4. “Assigns'
equal probabilities+to+
outcomes(when(they(
are$judged$to$be$
equipossible”"
(Wikipedia)

5. In#URLs,#content,#
locations)&)entities)
equiprobability-can-
be#problematic

6. This%could%be%in#The#
Web$of$Document$
(content)(or(The(Web(
of#Data#(entities,#
including(locations)

7. Where%two%or%more%domain%
assets,&surface&forms,&or&
entity&determinations&are&
considered)equal)a)
representative*is*‘the*chosen*
one’%(canonical)

8. Equiprobability-is-like-‘See-saw-SEO’

9. Nearest'Neighbours

10. All#the#pluralities#
are$clustered$
together'
(neighbours)"and$
one$is$picked

11. LaPlace’s)Principle)of)
Indifference

13. Where%there%is%equipossibility
there%is%a%need%for%further%
confirmations+beyond+the+
content&itself

14. One$must$
beat%the%
other

15. Sometimes(‘bits’(
are$picked$from$
multiple(
‘equiprobable,
outcomes’

16. Today’s(Topic:(Disambiguating(
equiprobability-for-improved-
search'performance

17. WHO
IS
DAWN
ANDERSON
@dawnieando
dawn.anderson@@move-it-
marketing.co.uk
move-it-marketing.co.uk
linkedin.com/in/msdawnanderson
Meet$Bert$&$Tedward
@dawnieando #FOS20

18. In#an#ideal#
world&
‘precision’+and+
‘recall’(would(
be#perfect…#
but…%it’s%NOT

19. So#search#engines#must#
also%work%off%probability%
determination

20. Using&‘The&Law&of&
Large&Numbers’&
(Educated)guesses))–
Progressively+learning

21. Google&Uses&(some)'Machine'Learning(for(Crawling,(Indexing(&(Ranking

22. On#the#‘long#tail’#
there’s'often'
very%little,%or%
nothing'in'it

23. Low$to$no$page!rank%pages%
(but%that%is%also%now%just%
one$of$very$many$things)

24. See!saw$SEO

25. When%the%canonical%
balance'tips'from'
equiprobability-
slightly

26. Your%ranking%flux%might%well%be%transferring%equiprobability

27. Several'types'of'
equiprobability-
ambiguitity may$cause$
your%project%to%
perform'less'well'
overall'in'search

28. Different(
types&of&
ambiguity)
can$impact$
SEO
Exact&duplicate&content
Near%duplicate%content
Natural'language'ambiguity
Generational*cruft*based*ambiguity
Machine(learned(ambiguity(‘lag’
Dot!to!dot$ambiguity
Semantic)heterogeneity
Location(based(ambiguity

29. Exact&duplicate&
content

32. Google&
probably(
chooses&the&
one$with$
highest'
‘probability’
Most%linked%to%internally
Most%linked%to%externally
Included(in(XML(sitemap
HTTPS
Prettier&URLs
Important)parent

33. Maybe&one&or&
several'of'many'
‘importance’-
factors

34. Google&works&this&
out$VERY$quickly

35. Near!duplicate*
content

36. It#starts#off#well#
enough…(but(over(
time

37. Google&realizes&
these%pages%are%
‘mostly’)the)
same%as%others

38. Some%
reasons
Many%matching%shingles
Quilting
‘Borrowed’)content)at)scale
Feeds
Big$Boilerplate$/$little$main$value
Data$driven$sites$with$little$value

39. Sometimes(these(are(sites(
trying'to'make'a'URL'
footprint(well(beyond(their(
contribution)to)a)positive)
‘Network)Effect’

40. Spoofing(the(
‘Network)Effect’

41. After&some&crawling&
&"sampling"Google"
puts%the%pieces%of%
the$puzzle$together

42. And$begins$to$
exclude'pages'
from%the%index

43. Exclusion*still*
happens…(A(LOT

44. I"ran"a"little"
Twitter'
competition)
with%only%
empathy(as(
the$prize

45. Some%of%the%
GSC$
‘exclusion’,
numbers(
were$huge…$
millions

46. And$even$over…$one$billion

47. Crawl&demand&
probably(
follows&the&
Pareto'Principle

48. Probably(20%(of(the(
URLs%satisfy%80%%of%
the$demand$&$
contribute*well*to*
‘The%Network%Effect’

49. Google&will&likely&use&
mostly'‘Sampling’'on'those''
heavy&‘excluded&URLs’

50. Looking'for'small'
samples'of'
content&&&URL&
patterns…)and…)
‘Discovered,,not,
crawled’)will)be)
high

51. ’Discovered,,
not$crawled’$
in#GSC#is#
Google&
saying…

52. They%know%what’s%
down%that%site%
section(or(URL(
parameter'path

53. The$verdict$is$
in

54. Those&URLs&will&be&
‘starved’*of*crawl

55. However'many'
times&you&submit&
and$inspect

56. Natural'
language'
ambiguity

57. For machines words are$
problematic.--Ambiguous…-
polysemous…*synonymous

58. In#spoken#word#it#is#
even$worse$because$of$
homophones(and(
prosody

59. Like%“four%
candles”)and)
“fork&handles”

60. Word’s'context'
(company)*helps&
enormously

61. Words&that&are&related&live&
near%each%other%in%
mathematical)spaces

62. “You%shall%know%a%
word%by%the%
company(it(keeps”(
(Firth,(1957)

63. Relatedness
First&level&
relatedness
Second'level'
relatedness

64. Co!
occurrence'
in#content#
helps&A&LOT
In#the#page#itself'(1st'level)
In#the#interconnected#pages&(2nd level)
In#the#subcategorization.(2nd level)
In#the#site#sections((2nd level)
In#the#external#relationships,(2nd level)
In#the#domain#ontology#as#a#whole&(2nd level)

65. Informational+content+
adds$to$the$contextual$2nd
level$relatedness$of$
transactional*content
Transactional+
content
Informational+
content

66. If#you#can#help#
with%
‘informational+
needs’&you&can&
‘probably’*help*
with%
transactional*
needs
Add#value#in#rich#
informational*
needs
Contextual*value*
passes%throughout%
the$whole$site

67. Adding&
Contextual*
Value&Does&
NOT$Mean
Adding&loads&of&content&below&
ecommerce&pagesAdding
Adding&‘LSI%keywords’%in#ecommerce#
pagesAdding

68. High%topical%
relatedness)
&"context"
vectors
Internal(linking
Not$spam

69. Utilise conceptual*
‘nearest(neighbours’
well

70. Utilise ‘Overflow*SEO’*as*
demand&&&content&
naturally(grows

71. Subcategories are one of the Kings

72. Merge%content%
which%is%‘too’%
conceptually+
very%similar%with%
no#separate#
demand

73. Google&may&realise&you&
can$‘probably’$help$with$
transactional*queries

74. Dot!to!dot$
ambiguity

75. Who$knows$what$
this%dot%to%dot%
puzzle&is&creating?

76. Absolutely*
no!one

77. If#you#chop#away#or#migrate#
half%of%your%website%then%
equiprobability-will-likely-be-a-
problem

78. A"half"drawn"website"
is#not#the#same#as#a#
fully%drawn%previous%
website?

79. Although(you(may(rank(‘marginally’(better(for(
fewer%things
Your%domain%‘topic’%
became&overall&more&
about&some&topics&&&less&
about&other&topics

81. Informational+
content&adds&
to#the#
contextual*2nd
level$
relatedness)of)
transactional*
content
Informational+
content
Transactional+
content

82. Prune,'Merge,'Improve,'Archive
Prune&– Only%
ballast
01
Merge%– Highly'
semantically+
related'content
02
Improve(–
Evergreen'pages'
worth&the&effort
03
Archive(– Older&
pieces&of&
temporal)content)
(like&a&library)
04

83. Avoid&removing&or&
hiding&user&
generated(content(
(except'spam)

84. Cruft&based&
ambiguity

85. Generational*cruft*
contributes+to+
equiprobability-
issues

86. Just%a%few%
examples…)
legacy'is'a'
problem
301$redirect$chains
Inconsistent)301s
No#301s#at#all
Canonical(points(to(a(301
Canonical(points(to(a(no!index
No!index&points&to&a&canonical

87. 301$Should$
Mean%The%
Resource(
Moved

88. You’re'saying'
things'(tokens'
(words),)topics,)
concepts,)
entities)'moved'
so#they#can#be#
re!filed

89. But$often$
there%is%little%
or#no#match#
at#all

90. Borderline)or)
true%‘soft%404’

91. Also,&any&legacy&canonicals&
are$now$defunct$by$the$
redirect'status

92. Cruft&&&migrations&
are$like$a$game$of$
rugby&as&the&ball&
(signals))is)passed)
between&URLs

93. A"sign"of"this"is"a"
temporarily+wrong+target+
ranking

94. One$URL$is$going$up.$$One$is$
going%down%as%signals%pass%
from%one%to%the%other%over%
time%– See!saw$SEO

95. Machine(
learned'
ambiguity)‘lag’

96. ALL#of#the#above#==

97. Crawl&Budget&
Woes%/%Learned%
Quality(Patterns

98. Your%
reputation*
precedes'you'
– You$are$
being&judged&
on#the#past

99. Your%quality(&(crawl will$be$
‘machine)learned’)by)‘Large)
Numbers’)over)time

100. Probably(you’ll(struggle(
to#get#enough#crawl#for#
Google&to&catch&up

101. You’ve'probably'got'
URLs%which%have%not%
been$crawled$for$years

103. Search'engines'realise there%is%
no#‘demand’#for#your#poopy#
pages’

104. Your%performance%will%be%based%on%what%is%indexed

105. Fear%not…%Small%
Wordpress(site

106. You$need$to$lure$
a"Grumpy"
Googlebot(with(
tasty%quality%
content&morsels

107. You$MUST$substantively,change,
the$ratio$of$poor$quality$to$high$
quality(in(the(site(as(a(whole(&"
add#more#value#OVERALL

108. Regain'the'crawl&and&get&more&
demand

109. Watch&for&
patterns((clues)(in(
GSC$Coverage$&$
take%a%demand!
driven'approach

110. In#transactional#pages#
identify(valuable(content,(
features(&(attributes(your(
audience(wants(

111. Pro!tip:%Adding%moooaaarrr
words&to&transactional&pages&
does%not%always%add%much%value

112. Plus…&There&is&often&a&
mathematically*natural*
ordered%pattern%to%things%
ranked'by'frequency

113. Like%word%
frequencies*
many%types%of%
‘ordered’'
popularities+will+
have%a%Zipfian%
Distribution

114. Where%the%frequency%of%
n"is#inversely#
proportional)to)its)
frequency)table)rank)–
1/n

115. Zipfian'
Distribution*
occurs&in&
many%other%
rankings(
unrelated)to)
language
Population*of*cities*in*a*country
Corporation)sizes
Income'rankings
No.$of$people$watching$same$TV$
channel

116. Nurture&internal&link&graph&
popularity*that*mirrors*
‘real&life&popularity

117. Popularity+&+Zipfian+Distributions
Is#it#really#
popular'in'
‘real&life’?
Does%it%follow%
‘The%Network%
Effect’?

118. Or#are#you#manipulating#it#for#
things'you'want'to'rank'for'
(which&aren’t&really&popular&at&
all)?

119. Building(genuine(
topical(hubs((Hub(&(
spoke)'(Strongly'
connected'
components)

120. Google&puts&the&pieces&of&the&
puzzle&together&slowly&but&
increases(with(quality(
improvements

121. Equipossibility goes%well%
beyond'duplicate'content'too

122. Semantic)
heterogeneity

123. Mis!matching)data)types)or)
equivalencies+in+data+tables+
from%same%or%other%domains

124. Linked'Data'has'been'around'for'a'long'time

125. There%have%historically%
been$several$ways$to$
implement(linked(data

126. Some%Types%of%Semantic%Web%Technologies%&%
Their&Markups
RDF SPARQL OWL SKOS
RDFa JSON!LD Microdata

127. Several'linked!data$types$&$web$
sources'come'together'causing'
equipossibility

128. Implementation+
Inconsistencies)Prevail)
(ed)

129. The$Knowledge$Graph$
&"Its"Data"Sources

130. The$majority$of$Google’s$entity$
types&reference&the&Wikipedia&
URI$or$the$Knowledge$Graph$MID

131. But$Now$Anything$Structured$Might$Be$Used

132. We#already#know#conversation#search#fills#gaps#via#web#information

133. The$web$is$a$‘Data$Lake’

134. Public'Datasets'(e.g.'Kaggle)'>'27k'datasets

135. Enter&Data&Search&by&Google&AI

136. Disambiguating+Data+
Sets%(is%hard)

137. I"asked"for"some"examples"on"Twitter

138. Example:)
Philosophers*Dates*
of#Birth#different#in#
Wikidata &"DBPedia

139. The$community$responded

140. 'Mashed!up’$
Knowledge)Graphs)
(Two%Don%Cherry’s%
and$his$dog’s$name$
! ‘Blue’

141. Image&Search&Got&Don&Cherry’s&Dog&Right

142. Wrong&price&included&in&images&from&other&sites

143. Images'from'
Direct'
Competitors

144. Edgar’s(Were(Comical

145. Van$Diesel$–
Death&– To#Be#
Advised??

146. Does%An%Ice%
Cube%Have%
Parents?

147. Teenage&
Mutant&Ninja&
Turtles(paint(
works&of&art

148. Wikipedia(Made(Their(Point(Well

149. A"six"legged"horse?

150. Somes&Reputable&
Knowledge)
Repositories)are)
Just%Plain%‘Wrong’

151. “Simply(saying(that(a(horse(
has$five$legs$doesn't$make$
it#true#– calling'a'horse's'
tail%a%leg%does%not%make%it%
one.”&(Wikipedia,&2019)

152. Equivalency,
between&data&
sources'is'sought

153. Efforts'Are'Underway'
to#Resolve
Since&2011&major&search&
engines&have&been&
focusing)on)Schema)
commonly

154. Google&
Deprecating+
Data!vocabulary*
Schema

155. Your%
Breadcrumbs+
Markup'May'
Be#Impacted

156. Entities'often'have'
many%surface%forms

157. Schema:SameAs and$OWL:SameAs

158. SameAs'Seems'To'Be'Effective

159. BE#consistent#in#ALL#
mentions(of(your(brand(
name%&%ALL%THINGS%
GENERALLY

160. Utilise'‘known’'
(popular))public)
datasets&&&knowledge&
repositories

161. Avoid&conflict&with&
‘known’'(popular)'
public'datasets'&'
‘knowledge*
repositories’

162. Realise well$
known%
knowledge)
repositories(
may$be$wrong

163. But$they$may$
conceptually+still+
be#‘right’"– They%
will$PROBABLY$win

164. Location(based(
ambiguity

165. Semantic)Heterogeneity)
is#a#problem#locally

166. Entity&
Address&
(location)*is*
a"VERY"Big"
Problem(
with%entity!
oriented(
search
street%number
Locality)! city%or%town
street/route(name,(if(detected
postal'code,'if'detected
country,)if)detected
broad_region+! administrative+area,+such+as+the+state,+if+
detected
Narrow_region+! smaller'administrative'area,'such'as'county,'
if#detected

167. Narrow_Region,
is#VERY#
Problematic
Inconsistent)data)from)
knowledge)repositories
Inconsistent)data)from)websites
Inconsistent)data)from)searchers
HUGELY'SPLIT'EQUIPROBABILITY

168. Which%
County'is'
Bristol(in?

169. Bristol(is(
BOTH%a%
county'and'a'
city

170. In#Scotland#and#Wales#
it’s%worse&(They&work&of&
a"different"regional"
division'system)

171. Google&Does&Not&
Understand)the)
Word%‘Historic'

172. What%about%
counties)that)
don’t&even&exist&
any$more?

173. At#least#this#
one$mentions$
London%as%well%
as#Middlesex

174. Everyone...)Is)
confused

175. Older&humans&
probably(keep(
ambiguous)
county'+'town'
combinations*
alive

176. In#location#focused#pages#adding#a#
postcode(could(be(much(more(valuable(
than%adding%lots%of%words

177. Contextual*relatedness*
in#local#spaces#is#
proximity!based

178. AreaServed Schema'&'Internal'
linking&by&Proximity&(e.g.&lat (x)$
&"long%(y))%is#powerful

179. Google&sometimes&puts&
the$pieces$of$the$puzzle$
together'sporadically

180. Align&ALL&the&
dots

181. Remember:'Consistency'is'one'of'the'Kings

182. Leave%no%room%for%
ambiguity

183. Keep$in$Touch
•@dawnieando
•@BeBertey

184. Some%Take%Aways

185. Go
• Watch&for&‘impact’&patterns&to&maximise upon%in%GSC%‘coverage’%reports
Optimise
• Be#careful#you#don’t#prune#away#second#level#relatedness#signals
Map
• Consider)Pareto’s)Law)when)identifying)issues)to)fix)in)GSC)coverage
Optimise
• Check&for&‘wrong&page&ranking’&due&to&cruft&&&lag&passing&signals
Get
• On#location#sites#consider#internal#linking#on#proximity
Identify
• Add#value#to#improve#on#‘The#Network#Effect’#in#attributes#&#informational#content
Use
• Make%it%obvious%you%can%‘probably’%help%with%transactional%needs%through%other%content