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MoDELS SIGNED

Metadata Distillery and ExpLoitation System

Total Cost €

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EC-Contrib. €

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Partnership

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Project "MoDELS" data sheet

The following table provides information about the project.

Coordinator
MEDIA DISTILLERY NEDERLAND BV 

Organization address
address: JOHN M. KEYNESPLEIN 12
city: AMSTERDAM
postcode: 1066 EP
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Project website https://www.mediadistillery.com/models/
 Total cost 1˙969˙937 €
 EC max contribution 1˙378˙956 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-2
 Funding Scheme SME-2
 Starting year 2018
 Duration (year-month-day) from 2018-08-01   to  2020-07-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    MEDIA DISTILLERY NEDERLAND BV NL (AMSTERDAM) coordinator 1˙378˙956.00

Map

 Project objective

Europe's media sector is strong in creating content but lacks behind in embracing new technologies and new business models. Competition from global players that are strong at technological innovation is increasing fast. This puts many jobs, original European content and cultural heritage at risk.

The future of broadcasters is in metadata management. This data is used to fuel media applications. These will be the backbone of future television and will be used to schedule programming, interactive programming, video discovery and targeted advertising. But still today, broadcasters rely on manual labelling by editors to tag the key content of their media. The holy grail here is to do this automatically, more extensively and in real-time.

We are Media Distillery and we developed a platform that analyses every millisecond of audio and video content in real-time. We produce the most extensive deep media metadata seen in the industry. By using cutting edge deep learning, artificial intelligence and state of the art data mining techniques, our platform filters all relevant information. The current Media Distillery Platform is already well proven in providing Media Metadata services, and we already serve ten international clients.

The aim of this project is to enhance and commercialize our Metadata Distillery and ExpLoitation System (MoDELS). This enables the widespread uptake of our Deep content understanding technology and associated applications. In this project we will demonstrate its effectiveness in four media applications at European TV operators. Demonstrating that with our advanced metadata, content catalogues are better managed, content descriptions are more accurate, searching is far more exhaustively and recommendations more useful. Hereby realising business opportunities for TV operators that were unimaginable before. They understand customers better, improve their business processes, increase revenue, reduce costs and improve decision making.

 Publications

year authors and title journal last update
List of publications.
2018 Evangelos Stromatias, Karthik Yadati, Martin Prins, Joost de Wit
Using machine learning to create personalised \'snackable\' content
published pages: , ISSN: 0000-0000, DOI:
IBC Conference 2018 2019-04-18

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The information about "MODELS" are provided by the European Opendata Portal: CORDIS opendata.

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