12. March 2018
Future digital perspectives: Austrian scientists develop pioneering analytics platform for TV content
Major EU funding for internationally leading expertise in media technology. Vienna-based MODUL Technology and webLyzard lead R&D and technology development.
Vienna, 7th March 2018 – A key concern of TV providers is to exploit the rapidly expanding opportunities arising from digital distribution channels. Now international experts, with significant contributions from Austrian partners MODUL Technology and webLyzard, are going to address this concern. With a funding of 3.5 million euros, the EU project ReTV will offer decision support to TV providers, together with tools to adapt existing content to a wide range of digital networks quickly and effectively.
Leading media technology experts across Europe have joined forces to enable TV providers to be more agile and responsive to increasing competition from new digital media. Their declared goal is to develop a “trans-vector platform” that provides TV providers with fast, reliable information on who consumes their content as well as when, where and how they do so. It will provide decision support regarding future publication of content on social networks and digital distribution channels, and where content adaptation is likely to pay off.
Dr. Lyndon Nixon, CTO of MODUL Technology and Assistant Professor at the Department of New Media Technology at MODUL University Vienna comments: “TV providers have to distribute their content through multiple channels such as social media, mobile apps, hybrid TV and digital archives. But compared to print media – which face similar pressures – their content is technically much more complex. Deciding which content should be adapted and in what way is therefore essential for meeting the demands of consumers in a cost-effective manner.”
This is where the ReTV project comes in. The project is coordinated by Vrije Universiteit Amsterdam, with MODUL Technology and webLyzard leading the R&D efforts and technical development, in collaboration with project partners from Germany, Switzerland, Greece and the Netherlands. The cooperative project is divided into three clearly defined sections, the results of which will be of significant value to TV providers. In addition to the “aggregation”, i.e. the creation of a steadily growing respository of TV-related online content, the “analysis” and “adaptation” of such content are key elements of the project.
AGGREGATION & ANNOTATION
More than 10,000 hours of video content and over 50 million documents will be collected and processed from news sources, social media and TV station websites every month. This huge volume of data will then be automatically analysed, and relevant metadata will be annotated to every document. Besides “hard” facts, such as links, names and salient visual features, the metadata will contain an automatic evaluation of online mood regarding the topics, persons or organisations mentioned in the content.
ANALYSIS & ADAPTATION
Professor Arno Scharl, Managing Director of webLyzard, describes how ReTV works: “In the analysis stage, the webLyzard platform is used to capture content trends across news and social media channels. This allows recommendations regarding both, the adaptation of existing content and the focus for new productions. Thereby ReTV will help optimise advertising strategies, for example by referencing relevant topics that are currently being actively discussed by consumers.”
ReTV will also provide predictions and suggestions regarding the optimal distribution schedule and the expected success of original and adapted content. The ongoing collection and processing of relevant data from a wide range of sources will enable the system to learn. Deviations between predicted and actual success will trigger automated optimisations.
Upon successful completion of the project, ReTV will strengthen the competitive situation of European media companies in today’s networked, global market for video content.
For images and further background go to: http://www.modultech.eu/media-resources
About ReTV: Enhancing and Re-Purposing TV Content for Trans-Vector Engagement
The ReTV project is an innovation project funded through the EU’s Horizon 2020 program (www.retv-project.eu). The project is coordinated by Vrije Universiteit (VU) Amsterdam (Netherlands). Other partners are MODUL Technology (Austria), webLyzard technology (Austria), CERTH – Center for Research and Technology Hellas (Greece), Genistat AG (Switzerland), the Netherlands Institute of Sound and Vision (Netherlands) and Rundfunk Berlin-Brandenburg (Germany). The project will run from January 2018 to December 2020 and is funded by the EU with 3.5 million euros.
About MODUL Technology GmbH
MODUL Technology (www.modultech.eu) is an R&D-Spinoff of the MODUL University Vienna (MU Vienna) focussing on multimedia applications, interactive TV and automated knowledge extraction. MU Vienna is an international private university in Austria owned by the Vienna Chamber of Commerce. It offers study programs (BBA, BSc, MSc, MBA and PhD programs) in the areas of international business and management, new media technology, public governance & administration and sustainable development, as well as tourism and hospitality management (www.modul.ac.at/study-programs). The university campus is located at Kahlenberg, in Vienna’s 19th district.
About webLyzard technology gmbh
webLyzard technology (www.weblyzard.com) is an Austria SME founded in 2008. Its award-winning Web intelligence platform detects emerging stories, visualizes semantic associations and provides one of the industry’s most advanced communication success metrics. The platform enables semantic search and visual media analytics solutions for international clients such as the United Nations Environment Programme (UNEP), the U.S. Department of Commerce (NOAA Climate.gov), and major business-to-consumer brands across various sectors. These solutions build on more than 15 years of R&D into text mining, information visualization, and the integration of semantic and geospatial Web technology.