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Proprietary and Confidential
Exploration is the New Search
/ Lora Aroyo
/ Vrije Universiteit Amsterdam
/ IBM Netherlands (CAS)
/ Tagasauris Inc
/ http://lora-aroyo.org
/ @laroyo
2
massive amount of online digital video content
3
online video content is 64% of Internet traffic
4
300h of video uploaded each min on YouTube
5
in 2020 it would take a person more than 5 million
years to watch the videos shared online in a month
6
there are videos out there
relevant to you …
7
but …
8
most online videos
NOT DESCRIBED
CAN’T BE FOUND
WON’T BE SEEN
9
what can we do
to describe videos better?
1
machine computation can do a lot
11
recognise objects & concepts
Proprietary and Confidential
unlock rich semantics
Proprietary and Confidential
12
Proprietary and Confidential
[setting] WESTERN
[character] DOLORES
[story arc] FLASHBACK 7
[object] TRAIN
[action] SHOOTOUT
[mood] SURREAL
[audience] SHOCKED
[extras] 22
[role] BYSTANDER
13
discover creative contexts
14
link across online videos
Proprietary and Confidential
15
put all that descriptive information together
to know what’s in a video
on a second-by-second basis
6
so, we can …
Proprietary and Confidential
16
add also behavioral information
to know how people watch & talk about videos
6
and, we can …
Proprietary and Confidential
Viewership
Channels profiles
Social Media Buzz
Audience Demographics
Audience Contexts
Platform profiles
17
all this will make
video search better
18
but we need more …
19
SEARCH vs. EXPLORATION
/ helps only when you know what to search for
/ assumes you understand a topic
/ accuracy driven
/ click-through driven
/ helps when you don’t know what to search for /
/ helps you understand & deepen in a topic /
/ serendipity driven /
/ focused on engagement /
20
what can we do
to support video exploration?
2
human computation can do a lot
2
CrowdTruth.org
bring more semantics of the real world
2
diversity	of	opinions,	sen)ments,	contexts	
collected	in	a	decentralized	way	
aggregated	views	over	collec1ons
introduces perspectives
http://crowdtruth.org
Proprietary and Confidential
24
consolidate	experts	&	end	users	perspec)ves		
for	con1nuous	improving	video	descrip1ons
25
humans & machines can go a long way
Proprietary and Confidential
HUMAN-IN-THE-LOOP AI FOR VIDEO EXPLORATION
/ Machines help to break-down video into granular moments, i.e. shots & scenes
/ Machines generate multitude of paths within and across videos
/ Humans perform simple actions, e.g. watching, following and rating a path
/ Machines generalise from these actions using explicit semantics
/ Machines learn to evolve & improve exploration path
/ Orchestrate a continuous human and machine symbiosis
/ The ultimate aim is to reach a tipping point for video exploration,
e.g. web search, speech recognition
2
to transform the online video experience
2
Multimedia Explorations for
Smart Culture
2
Interac1ve	Explora)on	&	Discovery	in	Context	
linking	objects	to	events	and	en&&es	
building	automa1c	storylines	(narra1ves)	on	topics	or	objects
Access	to	integrated	online	mul)media	collec1ons	
using	Linked	Open	Data	to	integrate	metadata	of	various	
heritage	collec1ons
DIVE+
Aggregated	views	over	the	collec1on	
collec1ng	perspec&ves	from	crowds	&	niches
http://diveproject.beeldengeluid.nl/
3
Erp,	M.	van;	Oomen,	J.;	Segers,	R.;	Akker,	C.	van	de;	Aroyo,	L.;	Jacobs,	G.;	Legêne,	S;	Meij,	L.	van	der;O	ssenbruggen,	J.R.	van;	Schreiber,	G.	
AutomaDc	Heritage	Metadata	Enrichment	with	Historic	Events	Museums	and	the	Web	2011	hKp://www.museumsandtheweb.com/mw2011/
papers/automaDc_heritage_metadata_enrichment_with_hi
31
types
32
filters
3
explore entities
related
entities
3
entity
exploration
3
object
exploration
3
people filter
3
event filter
3
narrative
3
4
Video Explorations with
Micro-moments
MOMENTS REDEFINE CURRENT VIDEO SEARCH
MOBILE/SOCIAL
OPTIMIZED
RELEVANT SEARCH RESULTS
PREVIEW SPECIFIC MOMENTS
OR WATCH FULL VIDEOS
DISCOVER ACTIONABLE
MOMENTS WITHIN VIDEO
MOMENTS: PERSONAL VIDEO CHANNEL
SEARCH FOR
ANYTHING, WITH
ANYTHING
HYPERMEDIA PLAYER
W/ LINKED MOMENTS &
FULL VIDEOS
AI ACTIVELY
LEARNS USER
PREFERENCES
DISCOVERS
MORE & MORE
CONTENT
AI, DEEP LEARNING & NETWORK EFFECTS
Ensemble algorithmic processing
Video, audio & text
Extract & understand entities
Does what computers are good at
AI & DEEP LEARNING:
//
//
// Human assisted computing
Collective intelligence (incl. fans)
Waze effect
Does what humans are good at
NETWORK EFFECTS:
//
//
//
OBSERVE & LEARN
VERIFY & EXTEND
*U.S. Patent Application #13/863,751
Web-scale layer of structured, linked data.
////
DOMAIN-SPECIFIC DATA
MOMENTS
4
4
4
Proprietary and Confidential
HUMAN-IN-THE-LOOP AI FOR VIDEO EXPLORATION
/ Machines help to break-down video into granular moments, i.e. shots & scenes
/ Machines generate multitude of paths within and across videos
/ Humans perform simple actions, e.g. watching, following and rating a path
/ Machines generalise from these actions using explicit semantics
/ Machines learn to evolve & improve exploration path
/ Orchestrate a continuous human and machine symbiosis
/ The ultimate aim is to reach a tipping point for video exploration,
e.g. web search, speech recognition
49
to explore strange new worlds ….
to boldly WATCH what no-one has WATCHED before
Proprietary and Confidential
Exploration is the New Search
/ Lora Aroyo
/ Vrije Universiteit Amsterdam
/ IBM Netherlands
/ Tagasauris Inc
/ http://lora-aroyo.org
/ @laroyo

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