Personalizing Media Interaction on the Web

© Kierstin Shaylee

Personalizing
Media
Interaction
on the Web

Lora Aroyo

Wednesday, October 3, 12 1

“interface is the message”

Aaron Koblin: Artfully visualizing our humanity, TED Talk, 2011
Lora Aroyo twitter: @laroyo

it’s complicated


HCI challenges
semantics
user data

pe int
rs er
on ac
tio
ali n
za
tio
n
Flickr: elkabong

semantic HCI challenge

• explicit semantics (often from open sources, e.g. LOD) used for
system decisions and results

• use facetted presentation, searching and browsing of information

• use typically classiﬁcations, typologies or other structures of concepts

• integrate & aggregate data from diﬀerent sources


user data HCI challenge


interaction HCI challenge
• search, e.g. keyword, faceted

• browse, story lines, narratives through collections

• annotations of multimedia, e.g. (collaborative) tagging,
professional annotation of text, images and video, tagging
games

• explanations, hints, user feedback, e.g. explanation of
recommendation results, explanation of autocompletion
suggestions


interaction with semantics


http://twitpic.com/il1w/full ©
BBC
MMVIII


http://www.bbc.co.uk/programmes/b00c06n2.rdf


personalization challenge

• data challenges multiply with Web openness
• social recommendations are preferred
• it is not about (single) algorithms any more
• it is about the metrics


applications


personalized TV

© Ugli. on the Walls of BBC London


User Perspective

• what is the role of social recommendations?
• how do people watch TV together?
• how devices inﬂuence watching?
• what are perceived trade-oﬀs for privacy vs. personalization?

Technology Perspective

• what is the role of metadata in TV & Apps?
• what are ways to share information in real time?
• what are ways to sync TV & other metadata?
• what is an easy way for devices to ﬁnd & talk to each other?

© VickyBuser, BBC

choices, choices ...

© RedBee Slides at MIPCube2012

lost in space


always missing something

demand for experience

© Ericsson ComsumerLab: TV & Web Consumer Trends 2011

Social Recommendations

I usually ﬁnd NEW programmes to watch by:

© NoTube Studies @ BBC

RESULTS OF NOTUBE SOCIAL WEB & TV SURVEY 2012


I usually ﬁnd NEW programmes to watch by:

© NoTube Studies @ BBC
Social TV




interface explorations


Linking Web Data to User Proﬁles


TV Preferences
• Inferred from the Social Web
• tweets, FB likes, last.fm listened, etc.
• weighted interests

• Represented using Linked Data web identiﬁers
• record-linkage: facebook.com/pages/ dbpedia.org/

• NLP: #littlebritain

http://dbpedia.org/resource/Matt_Lucas
http://dbpedia.org/resource/David_Walliams

TV Preferences
• Inferred from the Social Web
• tweets, FB likes, last.fm listened, etc.
• weighted interests

• Represented using Linked Data web identiﬁers
• record-linkage: facebook.com/pages/ dbpedia.org/

• NLP: #littlebritain Brilliant british humor by Matt Lucas & David
Walliams - whole range of facinating characters
portraying diversity of british society
http://dbpedia.org/resource/Matt_Lucas
http://dbpedia.org/resource/David_Walliams

http://xmlns.notu.be/aair/

http://xmlns.notu.be/wi

Semantic Content Semantic
Patterns for Pattern-based
TV Programs Recommendation
EPG Metadata TV Program
Strategy
(BBC) Enrichment
RDF Graph Statistical
TV Recommendation Similarity-based
Programs Service Recommendation
Strategy
User Ratings &
Demographics User Data Similarity
(BBC EPG Analysis Clusters Hybrid
Data) of Programs Recommendation
Strategy

End End-Users
Users


NoTube’s Beancounter
aggregate, analyze & proﬁle


NoTube’s User Activities
aggregate


NoTube’s User Interests
proﬁle


NoTube’s User Interests
analyze


NoTube’s User Explanations
control


Recommendations in NoTube

© Dan Brickley

• surface interesting, new & relevant programs to individual and group users
• combine in a complementary way diﬀerent statistical & semantic approaches
• deﬁne metrics for, e.g. serendipity, diversity, relevance

From Predictability to
Serendipity


Serendipity
Secret
Paul Merton Gardens
looks at
Alfred Hitchcock
Make ‘em
laugh


Serendipity
format
at documentary Secret
form form
Paul Merton at Gardens
looks at
Alfred Hitchcock
Make ‘em
laugh


Serendipity
at documentary format
Secret Basic patterns
form form
Paul Merton at Gardens
genre
looks at art culture ge
genre nr
Alfred Hitchcock aw and the media e
ard Make ‘em
award laugh
Grammy Awards homes and
gardens


Serendipity
form form
Paul Merton
genre
at Gardens Homogeneous patterns
genre nr
ard Make ‘em
an award laugh
ch
or gardens

Paul
Merton
pa
rtn
er

Caroline
Quentin
ac
to
r
ge
Life of nr
e
Riley

comedy


Serendipity
form form
Paul Merton
genre
genre nr
ard Make ‘em
an award laugh
ch
or gardens

Paul
Merton infl
uen
ce
pa
rtn
er Spike
act
Milligan or The adventures
Caroline of Barry
Quentin McKenzie
ac
to
r
ge
nre

Life of nr
form

e
ge

Riley
at

comedy

film


Serendipity
form form
Paul Merton
genre
Alfred Hitchcock aw and the media genre nr
e
Heterogeneous patterns
ard Make ‘em
an award laugh
ch
or gardens
synopsis
influence Charlie enrichment
Paul
Merton infl
uen Chaplin Shanghai
pa
ce Knights
rtn
er Spike gen
act re

at

form
Caroline of Barry action and
Quentin

ac
McKenzie adventure
ac

to
to

r
r
ge
nre

Life of nr
form

e
ge

Riley
at

comedy Jackie
Chan

film


Serendipity
form form
Paul Merton
genre
Alfred Hitchcock aw and the media genre nr
e
Heterogeneous patterns
ard Make ‘em
an award laugh
ch
synopsis or gardens
enrichment synopsis
influence Charlie enrichment
Paul
Merton infl
uen Chaplin Shanghai
pa
ce Knights
Alfred rtn
er Spike gen
Hitchcock act re

at

form
Caroline of Barry action and
director Quentin

ac
McKenzie adventure
ac

to
to

r
r
ge
nre

Life of nr
form
Suspicion e
ge

Riley
at
d

comedy Jackie
ar

ge

form Chan
aw

at
nre

Academy film
Awards Thriller


Weak Semantics & Strong
Statistics


Statistics

Paul Merton
looks at anchor Paul partner
Alfred Hitchcock Merton Caroline
Quentin

or
act
at
form

ge
nre

Life of
Riley
documentary

art culture
and the media


Statistics

Paul Merton woman
looks at anchor User
Alfred Hitchcock
Paul partner
Caroline 25 years old
Merton profile
Quentin 1 child

or
act
at
form

ge
nre

Life of
Riley
documentary

art culture
and the media


Statistics

Paul Merton woman
Alfred Hitchcock
Paul partner
Merton profile
Quentin 1 child

or
act
at
form

ge
nre

Life of
Riley
documentary

art culture
and the media
25 year old
women with
1 child


Statistics

Paul Merton woman
Alfred Hitchcock
Paul partner
Merton profile
Quentin 1 child

or
act
at
form

ge
nre

Life of
Riley
Similar users
documentary

art culture
and the media
25 year old
women with
1 child


NoTube’s N-Screen drag & drop, shuﬄe, sharing & TV control

N-Screen
drag & drop, sharing & TV control

NoTube’s N-Screen
similar programs


NoTube’s N-Screen random selection

• means of surfacing content buried in the video collection
• when users might reach a dead-end with the recommendations
• adds an extra element of serendipity

NoTube’s N-Screen
explanations

• depending on recommendation strategies
• depending on the user’s task

Focus Groups
http://notube.tv


finding

INTERESTING
PROGRAMMES

sharing them
♥ suggestions activities your past
'Social Web'
based on

♥
suggestions based on programmes
others have watched

linking programmes by guests, actors, ♥ drag & drop
✔ presenters etc.

✔ 'shuffle' option for programme selection
♥ ♥ swapping suggestions with specific friends

? explaining recommendations ? sharing suggestions with others in the same room

? sharing to watch immediately

controlling the TV
♥ drag & drop to change what's playing on TV

watching with friends
✔ watching 'together apart' in different locations
✘ changing programmes on someone else's TV

connected heritage

data: open, shared & accessible
infrastructures: interoperable
smart services: relevant content
in right context

enriching collections


discovering links
mili<a place:
Amsterdam,

1625
to
1650

studentOf:

Pieter
Lastman

self-‐portrait

teacherOf:

style:
Baroque Gerrit
Dou

The
Night
Watch

http://chip-project.org Lora Aroyo twitter: @laroyo

enriching with events


discovering links


personalized experience


http://chip-project.org

http://agora.cs.vu.nl


Yiwen Wang
Natalia
Roxane Stash
Segers
Iina Hellsten
Chiel van
den Akker Geertje Jacobs Frank de Bakker Marteen
Brinkerink
Bibiana
Armenta

Piek Vossen
Thomas Johan
Chris Welty Michiel
Guus Schreiber Ploeger Oomen
Hildebrand

Riste
Gligorov
Marieke
Lourens van Susan Jacco van Geert-Jan Lotte Belice
van Erp
der Meij Legêne Ossenbruggen Houben Baltussen

Questions?

@laroyo
http://lora-aroyo.org

Personalizing Media Interaction on the Web

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