TVOT June 2012
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Transcript of TVOT June 2012
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8 lessons from deploying Content
Discovery solution at Orange (France)
Dr. Ofer Weintraub
VP Innovation – Viaccess-Orca
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Who we are ?
Viaccess-Orca
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About
Founded – June 13 2012
350 employees
Offices: France, US, Hong-
Kong, Israel
100+ customers worldwide
Fully owned by France
Telecom
Flexible middleware platform delivering a full
array of IPTV & OTT services – including live TV,
VOD and PVR, across multiple screens
Personalized Content
Discovery platform that
recommends
the right content
TV Everywhere
CAS / DRM
Products
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Quick primer
Content Discovery
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RecommendationsSearch Exploration
I know what
I am looking for
The service knows
what I am looking for
I’d like to explore
with my personal guide
3 main ways to discover content
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3 main ways to discover content
Auto-complete
Auto-suggest
Social-aided
Personalized
search
Smart filters
Collaborative
filtering
NLP - semantic
Social
Popular/Trending
Lists (experts,
operator, users)
RecommendationsSearch Exploration
Personal zone
Games
Trends
Deals
Friends
Gossip
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Search example
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Recommendations example
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Explore example
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How it generally Works ?
Middleware
(CMS, CRM)
Usage
data
Event Registration
Engines
Discovery
Manager
User
Profiles
Collaborative
filtering
Advanced
semantic
Filtering
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Content Discovery for every service….
VOD Linear TV series
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… and on any device
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measuring the value of
Content Discovery system
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75% of what people watch is from
some sort of recommendation.
Netflix blog April 2012
35% of Amazon sales are due to
recommendations
Venturebeat - 2006
Nice numbers but no single way to measure success…
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Typical measures
Accuracy CoverageNovelty
SerendipitySatisfaction
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Testing methods
Train Predict
Subjective testing
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Lessons learned
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Lesson 1 –have a dedicated group of real users for tests
15%
15% satisfaction gain in 1 week by
adding bots and tuning thresholds
and filtering in collaborative-filtering
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Lesson 2 –avoiding the rotten
apple is more important
than getting the perfect
ones
We’ve seen dramatic jumps in
satisfaction when pruning bad
results
- Time slices
- Thresholds
- Exclude rules
- Adequate “system warming”
- External guides (e.g. popularity)
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Research: The Effect of Dual NetworksProf. J. Goldenberg, Dr. G Ostreicher and S Reichman - Feb. 2011
Multiple engines (i.e. engines blend ) help overcoming the
filter- bubble effect
Overall satisfaction
(1 – 10)
Rating
( 1- 5)
Single
Network 6.01 2.72
Dual
network 8.00 3.14
Change 33% ~15%
Semantic
Social
Lesson 3 –
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Research: Negotiation agents n=50 x 2 (US, India)Prof. S. Kraus and Dr. A. Hasidim - Apr. 2012 (not yet published)
Collaborative filtering is popularity biased,
users prefer novelty
Lesson 4 –
The highest correlation found in early experiments is
between novelty and purchase decision (0.55)
Which one to recommend if
score is the same ?
Avatar ?
The Pianist ?
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OMG it speaks FrenchLesson 5 –
Fearabhorrence, agitation, angst, anxiety, aversi
on,
awe, chickenheartedness, cold feet,cold sw
eat, concern, consternation, cowardice,cree
ps, despair, discomposure, dismay,disquiet
ude, distress, doubt, dread,faintheartednes
s, foreboding, fright, funk, horror,jitters, mis
giving, nightmare, panic, phobia,presentime
nt, qualm, recreancy, reverence,revulsion, s
care, suspicion, terror, timidity,trembling, tre
mor, trepidation, unease, uneasiness, worry
Peur
panique, phobie, frayeur, appréhension, frisson,
épouvante, crainte, alarme, émotion, affolement
Change in words statistics, change of sources
, change in amount of reviews, change of
vocabulary, correlation to English data is not
always clear
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Cold start could get really cold….Lesson 6 –
System bootstrap User cold start Content cold start
Add users
Add values
Hybrid methods
Non-personal
Implicit evidence
Questionnaire
Non-personal
Implicit evidence
Aggregated data
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Laziness wins….Lesson 7 –
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Privacy mattersLesson 8 –
Profile visibility
Explicit / Implicit- Channels
- Genres
- Actors
- Devices
- Subscriptions
- Black / White
lists
Enough value
when not opted-in
Still relevant
- Semantic without
history
- Popularity
- Trends
- Lists
- General CF
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Provide reason
Other points to consider
Collect valuable indirect evidence
Handle “time” with care
Recommended because 3 of
your friends liked it
VOD orderVOD content endVOD ratingAdd to wish listShow movie previewChannel zapping
Channel zappingProgram recordingSetting a reminderLaunches of COMPASSExplicit inputExclude contentSearch terms
Mo
rnin
g
No
on
Evenin
g
Nigh
t
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It’s an on going process
It’s getting better every month
It’s a lot of fun
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Anyone?
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