Keynote at SMAP2012: Personalized Access to TV Content

Personalizing TV Interaction with Social & Semantic WebLora Aroyo

VU University Amsterdam

@laroyoWednesday, December 12, 12

Wednesday, December 12, 12

Web vs. TV

TV is the Web

42% of UK adults who use Internet while watching TV also discuss or comment on programs they are watching

but ...

lost in space© RedBee Slides at MIPCube2012

demand for experienceWednesday, December 12, 12

Social Recommendations© Ericsson ComsumerLab: TV & Web Consumer Trends 2011

COMMUNITY-BASED EXPERIENCE

not a single TV-viewer activity any more

SOCIAL VIEWING SCENARIOS

for more details check out our blog at http://notube.tv

ADAPT INDIVIDUAL SECOND SCREEN EXPERIENCE

for more details check out our blog at http://notube.tv

Social & Personalized TV

http://notube.tvWednesday, December 12, 12

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?

NoTube’s Beancounteraggregate, analyze & profile

NoTube’s User Activitiesaggregate

NoTube’s User Interestsprofile

NoTube’s N-Screen

N-Screendrag & drop, sharing & TV control

drag & drop, shuffle, sharing & TV control

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?

• access to basic metadata about programs • links are the basic currency of social media

• URIs for the things you watch • links to related Web entities

• even a small amount of metadata enables interesting apps

Open Web Standards & Data

Recommendations in NoTube

• 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

TV Preference Data: Sparse & Fragmented

Even for a single service (e.g. Netflix) challenges multiply:

• often no global view, only per-user data

• many ways of identifying same content item

• many ways of identifying same user

• many ways of identifying entities e.g. actors, directors, ...

TV Preferences in NoTube

• Inferred from the Social Web

• tweets, FB likes, last.fm listened, etc.• weighted interests

• Represented using Linked Data web identifiers

• record-linkage:

• NLP:

facebook.com/pages/ dbpedia.org/

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

#littlebritain

TV Preferences in NoTube

• Inferred from the Social Web

• tweets, FB likes, last.fm listened, etc.• weighted interests

• Represented using Linked Data web identifiers

• record-linkage:

• NLP:

facebook.com/pages/ dbpedia.org/

Brilliant british humor by Matt Lucas & David Walliams - whole range of facinating characters portraying diversity of british society

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

#littlebritain

From Predictability to Serendipity

Paul Merton looks at

Alfred Hitchcock

SecretGardens

Make ‘em laugh

Alfred Hitchcock

SecretGardens

Make ‘em laugh

documentaryformat

format

homes and gardens

Grammy Awards

genre art culture and the media

Alfred Hitchcock

SecretGardens

Make ‘em laugh

Basic patternsdocumentaryformat

format

homes and gardens

Grammy Awards

PaulMerton

anchor

partner

CarolineQuentin

Life ofRiley

Alfred Hitchcock

SecretGardens

Make ‘em laugh

Basic patternsHomogeneous patterns

documentaryformat

format

comedy

homes and gardens

Grammy Awards

PaulMerton

anchor

partner

CarolineQuentin

Life ofRiley

SpikeMilligan

influence

The adventuresof Barry

McKenzie

e form

Alfred Hitchcock

SecretGardens

Make ‘em laugh

Basic patternsHomogeneous patterns

documentaryformat

format

comedy

homes and gardens

Grammy Awards

PaulMerton

anchor

partner

CarolineQuentin

Life ofRiley

SpikeMilligan

influence

McKenzie

e form

Alfred Hitchcock

SecretGardens

Make ‘em laugh

CharlieChaplin

synopsisenrichment

ShanghaiKnights

action andadventure

JackieChan

influence

Basic patternsHomogeneous patternsHeterogeneous patterns

documentaryformat

format

comedy

homes and gardens

Grammy Awards

PaulMerton

anchor

partner

CarolineQuentin

Life ofRiley

format

synopsisenrichment

Alfred Hitchcock

director

Suspicion

AcademyAwards

Thriller

SpikeMilligan

influence

McKenzie

e form

Alfred Hitchcock

SecretGardens

Make ‘em laugh

CharlieChaplin

synopsisenrichment

ShanghaiKnights

action andadventure

JackieChan

influence

Basic patternsHomogeneous patternsHeterogeneous patterns

documentaryformat

format

comedy

Weak Semantics & Strong Statistics

Paul Merton

looks at Alfred Hitchcock

PaulMerton

anchor partnerCarolineQuentin

Life ofRiley

ordocumentary

art culture and the media

genreWednesday, December 12, 12

Paul Merton

PaulMerton

Life ofRiley

ordocumentary

woman25 years old1 child

Userprofile

Paul Merton

PaulMerton

Life ofRiley

ordocumentary

25 year old women with

1 child

Userprofile

Paul Merton

PaulMerton

Life ofRiley

ordocumentary

25 year old women with

1 child

Similar users

Userprofile

Challenges

• data challenges multiply with Web openness

• serendipitous social recommendations are preferred

• it is not about (single) algorithms any more

• it is about the metricsWednesday, December 12, 12

INTERESTING PROGRAMMES

watching with friends

suggestions based on programmes others have watched

linking programmes by guests, actors, presenters etc.

sharing suggestions with others in the same room

watching 'together apart' in different locations

changing programmes on someone else's TV

♥♥

suggestions based on your past 'Social Web' activities

controlling the TV

drag & drop

swapping suggestions with specific friends

sharing them

sharing to watch immediately

http://notube.tv

? explaining recommendations

'shuffle' option for programme selection

finding

USER TESTING RESULTS December 2011, BBC R&D London10 participants : 5 male, 5 female, aged between 20 to 64

drag & drop to change what's playing on TV

♥ ✔ ✘ ? loved liked disliked unsure

For more details:

What’s now

• The move to IP - opportunity to discover what people watch in greater breadth and depth• gather consumers’ viewing behavior & video streams• combine them with enhanced EPG as input for a holistic live-stream data mining analysis

• generate a high-quality linked open dataset (LOD) describing live TV programming• market research on viewing behavior

Keynote at SMAP2012: Personalized Access to TV Content

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