NoTube: Stoneroos show case

WP7b
Personalized TV Guide with Adaptive
Advertising
Pieter Bellekens (Stoneroos), Myoung-Wan Koo (KT)
Stoneroos, Thomson Video Networks, Engin, KT

Outline

• WP7b Goals
• NoTube architecture
• Personal Recommendations
• Multi-device PPG application
• Multi-lingual applications
• DEMO: Personal advertisement
• Evaluation
• Concluding remarks

Stoneroos Interactive Television www.stoneroos.com

26-27 March 2012 NoTube 3rd review 2

WP7b Goals

1. Design and development of a Personalized Program Guide (PPG)
2. Recommendation system for TV programs
3. Multi-modal and multi-device aspects of a PPG
4. Multi-lingual PPG environment
5. Personalized product placement in video streams



NoTube
Architecture
WP 7b
Multi-platform,
Multi-Lingual and
Multi-modal interfacing

Recommendations as
essential part of
Personalization

Keep track of the user

Keep track of all sorts
of heterogeneous data



NoTube
Architecture

Frontend
• As an application within the
NoTube Architecture
• Integration with the
NoTube User Portal via API



Goal1+2: Personal Recommendations

Design and development of a Recommendation system
Personalized for TV programs
Program Guide



WP7b Recommendations

Weighted content-based recommendation algorithm combined with
collaborative filtering and kickstarted by demographic filtering

• Properties of content are compared to the user profile where we
maintain the user’s feedback with respect to these properties
• Different properties have different weights reflecting their importance
• Feedback is obtained both implicitly and explicitly, and in a context-
sensitive manner
• Demographic filtering used to tackle cold start problem
• Explanations of recommendation to enlighten users in the algorithm’s
working



WP7b Recommendations

User Profile

22 Demographics used for
demographic filtering

Likings (optionally contextualized)
used for content-based and
collaborative filtering



Goal 3: Ubiquitous PPG

Multi-modal and multi-device aspects of a
Personalized Program Guide

Yahoo TV Widget

iPhone app KT’s iPad app



Goal 4: Multi-lingual interfaces

Multi-lingual Program
Guide environment Korean

Turkish

German



Multimodal/Multilingual
Interface in KT


Interface in KT
• Search Server
– Search and show IPTV contents on mobile devices
( Smart Pad, Smart Phone)
• 8000+ VODs, Live Channels
– Semantic Search by genre, topic, etc. as well as by
movie title.
• 8000 in Korean, 500 genre & topics

Interface in KT
• Multilingual Interface
– Multilingual search by WordNet-based translation
• Concept by WordNet,
• Synopsis & title in English from KMDB
• 1000 in English , 80 genre & topic
• Multimodal Interface for English
– To Recognize by AT&T Speech Mashup Server
• Include Only 80 words by performance problem

원호경 draugydoB
관찰경 nameciloP
제경 c i mon ocE
혼결 e g ai r r a M
기투격
울겨 r e t ni W
임게 e ma G
샤이게 a h si e G
사검 r ot u c es or p
전프걸
북거 e si o t r o t
Humming 단갱 gna G
미개 tnA
허밍
When I turned nice 아홉 살 인생 개 goD
The Foul King 정감 g nil e e F
옥감 n o si r P
반칙왕
Winter Sonata 사호간 es r u N
력 폭 정 가 e c n el oi V c i t s e m o D
겨울 연가
Short Time 이대로, 죽을 순 없다
부정가 repeekesuoH
Enjoy Life 을가 llaF
수가 r e g ni S
살 맛 납니다
English Title Korean Title 재소 어영 NW
Interface in KT

Goal 5: Personalized ad placement [DEMO]

Personalized product placement in video
streams

Integration
with second screen to enhance experience


Evaluation

• Evaluation of the “Why is this recommended” feature
o GOAL: To find out whether providing feedback to the users is actually
useful, appreciated, improving user satisfaction, etc.
o In cooperation with TU/e
o From 312 recruited users, 97 participated throughout the entire study,
which lasted a full week
o At the end a questionnaire was filled-in
o Users were divided in 4 slightly different application incarnations:

CB Recomm off CB Recomm on
Explanation off 1*
1 3
Explanation on 2 4
* The baseline where only demographic filtering was used


Evaluation



Evaluation results

• Trust:
o User’s trust in the system slightly decreased when explanations are shown
o However, trust improved when people use the system more frequently
• Perceived System Quality:
o Users with higher activity generally perceived the system of higher quality
• Choice Satisfaction:
o Results show an increase in choice satisfaction with explanations shown
o Again this result was much stronger for people active in the system
• Understandability:
o Results indicate that people understand the system more when they use
the system more frequently, and especially when explanations are shown

• Evaluation of the ad insertion technology from Thomson shown in WP4



Concluding remarks

• Life after NoTube
• Active during NoTube
• NoTube impact factor
• Linked in NoTube
• Learned during NoTube
• In retrospect: novel features



Life after NoTube

• Knowledge acquired within the NoTube project is currently exploited and
extended in present (and future) projects:
• Extending the recommendation algorithm to catch and filter even more
user-generated events, and are tailoring the technology for next generation
devices
• Enriching content by including social media information
as well as visual data including short movies and images
• Investigating the HbbTV standard (which is gaining
popularity) to see how we can further improve the TV
experience by means of personalization and Web content
• Launch of EPGdata, a TV metadata delivery platform
available at http://www.epgdata.tv/
• Main working partners include the big telecom providers among
which we are working with Tele2, KPN, Espial, Vodafone, etc.


Life after NoTube cont.

• International:
• Scanning the Turkish market, together with Engin, to search for business
and market opportunities
• Launching Turkish metadata
within the developed EPGdata
metadata framework
• Investigation towards other
potential TV metadata buyers
across the world



Active during NoTube 2011

• Participated in the IBC2011 booth
• Where we presented the VOD demo
together with Thomson Video Networks
and KT
• Joined advertising of the NoTube concept
and architecture
• Submitted and presented a publication at the
EuroITV 2011 conference
• “iTV in the Industry” track
• Poster submission titled: “Inclusion of
multiple devices, languages and
advertisements in iFanzy, a personalized
EPG”
• Creation of the Ad insertion demo video


NoTube Impact Factor

• Impact on standards and tech communities:
• Showcase proving the use of egtaMETA (A set of semantically defined
attributes considered to sufficiently describe advertising material)
[http://tech.ebu.ch/egtameta]
• Further prove that the use of Semantic Web technologies (like RDF,
OWL, etc.) is beneficial in domains with complicated data structures and
hard to come by metadata
• Further support to the TV-Anytime specification,
describing audiovisual content
• Extra showcases and requirement specifications
as input to the HbbTV consortium (e.g. apps,
profiling, recommendations, data enrichment, etc.)
• Proving the use and benefits of the social TV concept
to a broader audience


Linked in NoTube

• Integration with other WP’s
• Provisioning of and mappings between metadata specifications (IRT)
• Technology and services to place audiovisual material (in this case ads)
within a video streams (Thomson Video Networks)
• Utilisation of the Semantic Broker for enriched TV data (OU)
• Integration of the VOD portal in the NoTube user portal (Polymedia)
• Integration with specific partners
• Turkish metadata provisioning (Engin)
• Ad inclusion technology (Thomson Video Networks)
• Multi-model iPad app integrated with the VOD portal (KT)



Learned during NoTube

• That besides the proven advantages of the linked open data approach, also
some challenges emerge with respect to the size of the data sets and how to
retrieve the necessary information in a quick and responsive way
• There is a clear difference between requirements set by a customer who
knows what he wants and requirements at the start of a research project. For
the latter, during the course of a project technology continues to evolve which
can lead to new ideas/insights (e.g. emerge of the tablet)
• During NoTube we gained a great deal of knowledge concerning
apps development and business models on both mobiles, tablets
and connected TVs
• The fact that personalization and providing recommendations
on a TV platform is still a challenging and mind-breaking issue


In retrospect: novel features

• Creation of a TV recommendation system running on top of open
heterogeneous information through Semantic Web technologies
• Enrolment of a PPG system on several platforms (including mobiles,
connected TV, tablets, etc.), all closely integrated and contributing to a
richer user profile
• Integration of next-generation user-computer interaction through
multi-modal technology
• Automatic and personalized ad placement in video streams potentially
providing next generation business models.
• New insights into future metadata modeling for audiovisual material as
well as advertisements
• Insights have led to a EU patent on a personalized EPG interface



NoTube: Stoneroos show case

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NoTube: Stoneroos show case