Knowledge graphs for search & discovery

ⓒ 2018, Kiwisoft, all rights reserved
Aurélien Géron, May 31st
2018
Knowledge Graphs
& Deep Learning
@ YouTube

Generic Recs

Personnalized Recs

Collaborative Filtering

? ? ?
Collaborative Filtering
?

Deep Learning for Recommendations
https://research.google.com/pubs/archive/45530.pdf

Source: figure 3 from “Deep Neural Networks for
YouTube Recommendations”, by Paul Covington, Jay
Adams and Emre Sargin:

? ? ?
Cold Start Problem
?

Cold Start Problem
?
?
?
?

Rescued by Entities

topic vector
Source: figure 3 from “Deep Neural Networks for
YouTube Recommendations”, by Paul Covington, Jay
Adams and Emre Sargin:
The topic vector block is not in the original figure.

Visual Content Analysis (VCA)
Right image by Aphex34: https://commons.wikimedia.org/wiki/File:Typical_cnn.png
Deep Convolutional Neural Network
Left image from video: https://www.youtube.com/watch?v=EZEgz50VMsk

Large-scale Video Classification with Convolutional Neural Networks, CVPR 2014
https://youtu.be/qrzQ_AB1DZk
Visual Content Analysis (VCA)

Entity Linking using Textual Metadata

Wikipedia: Knowledge for Humans

Wikidata: Knowledge for Machines

Wikidata: Statements

PropertyEntity Value
Triple

P31Q2831 Q5
Michael Jackson Human
instance of

Wikidata: Graph of Entities
P19
P569
Aug
29th
1958
description
Q2831
“American singer and dancer” (en)
“歌手” (ja)
“அெம க பாடக ” (ta)
date of birth
place of birth
Michael
Jackson
Gary
P17country
Q30
U.S.A.
P625
Q184116
41°34'51"N
87°20'44"Wlocation

Wikidata: SPARQL
https://query.wikidata.org/

Wikidata: SPARQL

import requests
SPARQL_URL = "https://query.wikidata.org/sparql"
query = "SELECT ?coordinates WHERE {...}"
params = {"query": query, "format": "json"}
response = requests.get(SPARQL_URL, params=params).json()
print(response["results"]["bindings"][0]["coordinates"]["value"])
$ python wikidata_demo.py
Point(-87.345555555 41.580833333)
Wikidata: Query using Python
wikidata_demo.py

Search: Knowledge Panels

Structured Discovery

Q592031
(Wingsuit flying)

Q612
(Dubai)
Q592031
(Wingsuit flying)

Q592031
(Wingsuit flying)
Q309162
(Extreme sport)
Q809831
(BASE jumping)
Q193210
(Skydiving)
Q612
(Dubai)

Q592031
(Wingsuit flying)
Q309162
(Extreme sport)
Q809831
(BASE jumping)
Q193210
(Skydiving)
Q612
(Dubai)
???

Q592031
(Wingsuit flying)
Q309162
(Extreme sport)
Q809831
(BASE jumping)
Q193210
(Skydiving)
Q612
(Dubai)
Q1409571 German screenwriter
Q1686732 German catholic priest
Q2150539 German journalist, author and stage director
Q2150541 German farmer and politician (KPD)
Q2150546 German football manager
Q6108620 American botanist (1890-1970)
Q18815147 German classical philologist and teacher
Q24018780 Swedish-German artist

Q592031
(Wingsuit flying)
Q309162
(Extreme sport)
Q809831
(BASE jumping)
Q193210
(Skydiving)
Q612
(Dubai)
Q35127
(website)
Q918
(Twitter)
Q355
(Facebook)
Q34508
(Video)

Mention Detection Disambiguation Pruning

LSTM LSTM
LSTM LSTM
LSTM
LSTM
LSTM
LSTM
Entity Recognition Using Deep Learning
Washington and New York
LSTM
LSTM LSTM
Softmax Softmax
0
LSTM
LSTM
Softmax
B-LOC
LSTM
LSTM
Softmax
I-LOC
LSTM
B-LOC

Entity Linking Using Contextual Signals
?

Entity Linking Using Contextual Signals

Ranking Candidate Entities
VCA
Text
Ctx

Q592031
(Wingsuit flying)
Q309162
(Extreme sport)
Q612
(Dubai)
Q809831
(BASE jumping)
VCA
Text
Ctx
Q193210
(Skydiving)

Q592031
(Wingsuit flying)
Q309162
(Extreme sport)
Q612
(Dubai)
Q809831
(BASE jumping)
VCA
Text
Ctx
Q193210
(Skydiving)
Q592031
(Wingsuit flying)
Q612
(Dubai)
Q193210
(Skydiving)
Q309162
(Extreme sport)
Q809831
(BASE jumping)

Please watch the video and tell us which of the
following topics it is about:
● BASE jumping
● Dubai
● Extreme sport
● Skydiving
● Wingsuit flying
Human Evaluations
Central Off-TopicSecondary

Entity Linking Using Deep Learning
https://goo.gl/Q39di0
List of papers by Amund Tveit on
Deep Learning for
Entity Linking

https://github.com/ageron/handson-ml

https://youtube.com/c/AurelienGeron

Thank you!

Knowledge graphs for search & discovery

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