MyMedia contributes to TV-Anytime metadata standards
July, 2010
European Telecommunications Standards Institute (ETSI) has published updated versions of two
TV-Anytime metadata specifications which include contributions from the MyMedia project.
TV-Anytime is a set of globally-applicable metadata standards designed for broadcast services and IPTV.
The MyMedia extensions to TV-Anytime enhance the collection of user feedback and introduce support for
personalised recommendations.
ETSI TS 102 822-3-1 V1.6.1 (2010-07)
Broadcast and On-line Services: Search, select, and rightful use of content on personal storage systems ("TV-Anytime");
Part 3: Metadata; Sub-part 1: Phase 1 - Metadata schemas
ETSI TS 102 822-3-1 V1.6.1 (2010-07)
ETSI TS 102 822-6-1 V1.6.1 (2010-07)
Broadcast and On-line Services: Search, select, and rightful use of content on personal storage systems ("TV-Anytime");
Part 6: Delivery of metadata over a bi-directional network; Sub-part 1: Service and transport
ETSI TS 102 822-6-1 V1.6.1 (2010-07)
Steffen Rendle and Prof. Dr. Dr. Lars Schmidt-Thieme win the Best Student
Paper Award at WSDM 2010 in New York
February 8th, 2010
The MyMedia consortium gives its warmest congratulations to Steffen Rendle
and Prof. Dr. Dr. Lars Schmidt-Thieme from MyMedia partner University of
Hildesheim for winning the Best Student Paper award at the 3rd ACM conference on
Web Search and Data Mining (WSDM 2010) in New York. Their paper
Pairwise
Interaction Tensor Factorization for Personalized Tag Recommendation convinced
the jury of the WSDM which is a rather new, but highly competitive conference
(acceptance rate of 15%) about the intersection of research in information
retrieval and data mining with a balanced audience from industrial and academic
research.
About MyMedia
Problem Field
We are drowning in a sea of information overload. Television channels,
books and music assault our senses with far too much content. The volume of
content on the internet is literally exploding. Not only traditional media
but millions of individual users are putting their own content on the web.
The massive popularity of YouTube is just one example of this phenomenon.
So, in this flood, how do you find content that matters to you? How do you
discover multimedia information and entertainment in a way that suits you
personally? Isn’t there an easier way? MyMedia recommendations will help
solve this “crisis of choice”.
Solution
Finding what interests you doesn’t have to be an accident. The research
project MyMedia is researching solutions that jump beyond traditional
recommender systems which are based on a single multimedia source. MyMedia
provides recommendations to you that are integrated from many sources. You
personalize the system by simply indicating you like a particular video or
audio cast and it will find similar content. It will even learn what you
like on its own. The more you use it the more it knows your preferences.
Personalized recommender technology have the potential to become the central
experience for how users access multimedia content.
Beyond State of the Art Research
The MyMedia project seeks to advance the state of the art in several areas
including creating a software framework for building recommender systems,
creating a protocol for plugging in multiple content catalogs, and pluggable
recommender algorithms that can be targeted at specific needs. The project
will work on new algorithms, new ways to model user preferences, provide the
ability to incorporate aspects of social networking to create media centric
communities, and research enhancements in the use of metadata for
recommender systems.
Partners
The European Microsoft Innovation Center, BBC Research, BT Research,
Microgénesis, Telematica Instituut and the Universities of Hildesheim and
Eindhoven join their expertise in the MyMedia project t
o pioneer new dynamic
personalization software.
Results
The resulting system will allow easy integration
of multiple content catalogues and recommender algorithms in a single system
and provide technology for ranking the content based on personal
preferences. The system will learn from user behavior and enable the sharing
of recommendation results with friends and family while observing privacy.
MyMedia technology will be evaluated on its effectiveness and user
friendliness via scientific analysis tools and field trials in several
European countries.