Conversational Search, Entities, and Knowledge Graph - Mozcon 2014

Justin Briggs
Justin BriggsCEO & Founder at Briggsby
#MozCon
Justin Briggs • Getty Images
Talking Back to Conversational Search
@justinrbriggs • justin.briggs@gettyimages.com
Working in SEO
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Exciting time for SEO
Web Search
Page Page Page
Search in web, against documents
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
“What is limburger”
“Play say it ain’t so”
“Schedule a meeting with Lynn”
“Navigate to grandma’s house”
These queries never touch the web
Search
Web Email
Search against capabilities
Knowledge
Graph
Schema
Mobile
Apps
Documents Databases Applications
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Understanding natural language
Breaking down strings

#1 Tokenization

#2 Parts of speech tagging

#3 Lemmatization
#4 Named entity detection
#1 Tokenization
Who directed pulp fiction
#2 Parts of speech tagging
#2 Parts of speech tagging
Who directed pulp fiction
WP VBD NNP
WP: wh-pronoun
VBD: verb, past tense
NNP: noun, proper, singular
#3 Lemmatization
am, are, is => be
car, cars, car’s, cars’ => car
#3 Lemmatization
Converting to canonical words
#4 Named entity detection
photos of Emma Watson
opennlp.apache.org
String tokens[] =
tokenizer.tokenize("An input sample sentence.");
"An", "input", "sample", "sentence", "."
opennlp.apache.org
Photos of Emma Watson
Photos of <START:person>Emma Watson<END>
Knowledge graph capability
Replicate using mql
https://www.googleapis.com/freebase/v1/
mqlread?query={<insert query here>}
Strings to things
[{
"!/film/film/directed_by": [{
"/type/object/name": "pulp fiction",
"/type/object/type": "/film/film"
}],
"/type/object/name": [{}],
"/type/object/type": "/people/person"
}]
Question: Who directed the movie Pulp Fiction?
Answering queries without pages
{
"result": [
{
"!/film/film/directed_by": [
{
"/type/object/type": "/film/film",
"/type/object/name": "Pulp Fiction"
}
],
"/type/object/type": "/people/person",
"/type/object/name": [
{
"lang": "/lang/en",
"type": "/type/text",
"value": "Quentin Tarantino"
}
Answer: Quentin Tarantino
quepy.machinalis.com
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Curating entity content
Attributes and connections
Emma Watson
Born: April 15, 1990 (age 24)
From: Paris, France
Which Brad Pitt?
Next level keyword targeting
Actor: actor, producer, Angelina Jolie, 1963, Fight Club
Boxer: martial arts, boxing, Olympics, 1981
Find common attributes by type
Dynamic targeting using entity attributes
<Name> (# <Number>) : <Position> for <Team>in <City>, <State>
Dynamic targeting using categories
Emma Watson Photos - News, Publicity, Event, & Premiere Pictures
!
Seattle Seahawks Photos - Team, Player, & Fan Pictures
!
Justin Bieber Photos - News, Concert, & Fan Pictures
!
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Marking up schema
Schema takes you from web to data
JSON-LD: JSON-based linked data format
<script type="application/ld+json">
{
"@context": "http://schema.org",
"@type": "Person",
"name": "John Doe",
"jobTitle": "Graduate research assistant",
"affiliation": "University of Dreams",
"url": "http://www.example.com",
"address": {
"@type": "PostalAddress",
"streetAddress": "1234 Peach Drive",
"addressLocality": "Wonderland",
"addressRegion": "Georgia"
}
}
</script>
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Conversational Search, Entities, and Knowledge Graph - Mozcon 2014
Exciting time for SEO
Feels like we’re over here
We’re actually over here
Getting to AI faster
#MozCon
Justin Briggs • Getty Images
@justinrbriggs • justin.briggs@gettyimages.com
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Conversational Search, Entities, and Knowledge Graph - Mozcon 2014