In AI4Green, the latest program for research funding in Austria managed by the FFG, MODUL Technology is excited to begin a new funded project called SDG-HUB in which it will build a Knowledge Graph for the Sustainable Development Goals (SDGs) in Austria.

Having started in May 2022, the three-year project’s goal is to support Austria’s achievement of the SDGs of the Agenda 2030 through building a knowledge repository with AI-based semantic search and visualization capabilities. The repository will offer concrete insights into citizen and stakeholder perceptions via monitoring of the online discourse as well as measure progress towards achieving the Agenda 2030 and Paris Agreement on climate change mitigation via online data ingestion and analysis. Through a better understanding of the social mood and environmental indicators, national research and scientific communities will be enabled to communicate more effectively to citizens about both proper and improper behavior and contribute to measurable improvements in achieving climate and sustainability goals in Austria.

Together with the Zentralanstalt für Meteorologie und Geodynamik (ZAMG), the Climate Change Centre Austria (CCCA), the University of Innsbruck as well as project coordinator and long-time collaborator webLyzard technology, MODUL Technology provides competencies in Automatic Knowledge Graph Construction (AKGC), Word Sense Disambiguation (WSD) and relation extraction (Slot Filling). These will be used to build an SDG-HUB Knowledge Graph that provides disambiguated identities for all concepts that form part of the SDG discussion (particularly national and regional concepts that would be missing from global graphs such as DBPedia or Wikidata). Complemented by facts extracted from online sources about each concept, the SDG-HUB Knowledge Graph will support a sophisticated understanding of the online discourse and social mood around problems and solutions for meeting Austria’s climate and sustainability goals.

We hope this to be the first of many projects for MODUL University’s research centre to build domain-specific and national/regional Knowledge Graphs for different purposes. MODUL Technology can apply the same technologies and methodologies – plus lessons learnt in SDG-HUB – to support its future knowledge extraction and modelling work.

MODUL Technology : https://www.modultech.eu

SDG-HUB project: http://www.sdghub.at

Contact: Asst.-Prof. Dr Lyndon Nixon, nixon@modultech.eu  

The EU’s Horizon Europe programme funding research and innovation is coming to an end, and one of the last Horizon Europe projects supporting the media industry also recently came to a successful conclusion. ReTV stood for “re-inventing television for the interactive age”. With dropping viewing time for traditional broadcast TV and an audience shifting to online streaming, Europe’s media industry needs to adapt to distributing their videos in multiple digital channels like Instagram and TikTok and needs tools to help them publish the right video at the right time to get the attention of an online audience overwhelmed by content availability.

It was led by MODUL Technology – the research spin-out of MODUL University Vienna where faculty and researchers collaborate to innovate in new media technologies. A cross-European consortium developed online services and software that help media organizations such as broadcasters to identify the topics of heightened interest to their audiences, find media assets in their collections related to those topics, adapt media content for publication on digital channels such as social networks and schedule the optimal time to publish. MODUL brought data science and AI innovation to the project work, backed by its access to a huge scale data collection and annotation pipeline which provides millions of Webpage texts and social media posts for analysis.

Firstly, we have developed a large knowledge base of global and local events. Media organizations benefit from knowing about future events relevant to their audiences, and we can configure event listings to the interests of each audience. Secondly, we provide advanced components for data analysis that can extract the most significant keywords, topics and stories from the stream of online content. Thirdly, we combine our knowledge of events and topics over time with the latest techniques in machine learning and deep learning to provide topic prediction capabilities, i.e. suggest the topics that will be popular with the audience at a future date. All of our knowledge modelling, knowledge extraction and predictive analytics capabilities continue to be used in other ongoing projects in diverse areas such as brand communication, mobility and digital marketing.

Finally, MODUL Technology demonstrated its capacity to professionally co-ordinate a large EU project through to its successful conclusion. As is written in the project’s final review report, a group of experts evaluated the results of ReTV and stated: “The project has delivered exceptional results with significant immediate or potential impact on relevant stakeholders, namely, content producers, distributors, and broadcasters. The results can bring innovation and competitiveness advantage to those stakeholders by providing them the ability to identify trends and relevant content in a semi-automated or assisted manner, consequently producing and publishing content through the best channels and meeting users’ expectations.“

While we are proud of the results of ReTV and the successful co-ordination by MODUL Technology, now it is time for the team behind this research spin-out of MODUL University Vienna to continue to innovate in data science and AI, and look forward to new challenges funded by the soon-to-be-launched EU Horizon Europe funding program.

Contact for ReTV and MODUL Technology: Asst.Prof. Dr. Lyndon Nixon, nixon AT modultech DOT eu

A key concern of TV providers is to exploit the rapidly expanding digital possibilities for networking and publishing quickly and accurately. Now international experts, with significant contributions from Austrian partners MODUL Technology and webLyzard, are beginning to address this problem. The EU project ReTV, funded to the tune of 3.5 million euros, will provide TV providers with a basis for decision-making with a view to adapting existing content to today’s enormous range of digital networks quickly and efficiently.                                                      

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 enable providers to make sound decision-making about future publication of content on those social networks and digital distribution channels as well as where content adaptation is likely to pay off.

Targeted Adaptation

Dr. Lyndon Nixon, CTO of MODUL Technology and assistant professor at the Institute for 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 MODUL Technology, collaborating with webLyzard and other 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 enormous value to TV providers. In addition to “aggregation”, i.e. the establishment of a steadily growing directory of TV content, “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 appended to every document. Besides “hard” facts, such as links, names and salient visual features, the metadata contain an automatic evaluation of online mood regarding the topics, persons or organizations mentioned in the content. 

Analysis & Adaptation

Professor Arno Scharl, Managing Director of collaborating partner webLyzard technology, describes how ReTV works: “In the analytical stage, the webLyzard platform is used to capture content trends in social media. This allows intelligent recommendations to be made regarding the adaptation of existing content and the focus for new productions. In this way ReTV will help to optimise advertising strategies, for example by referencing socially relevant topics that are currently being actively discussed by consumers.”

In addition, ReTV will make forecasts about the optimal timing of the release and expected success of original and adapted content. Thanks to the continuous collection and processing of relevant data from a wide range of different sources, the system is also able to learn. If the actual success achieved deviates from predictions, the system will automatically be optimised. In the coming years, ReTV will thus strengthen the competitive situation of European media companies in today’s networked, global market for video content.

In January 2016, MODUL Technology GmbH welcomed its first new year 2016 its first self-acquired EU research project: In Video Veritas (InVID)!

InVID sets out to solve a very difficult problem: verifying the truthfulness of video content posted on social networks which claim to show news events. News agencies have to repeatedly deal with fake, manipulated or misrepresented videos being spread online in the aftermath of a news story. To retain their viewers’ trust, they want to be sure of the authenticity of such video before using it in their news reporting. InVID will provide a complete toolset, driven by various innovative technologies, to aid journalists and newsrooms in semi-automatically determining if a video is trustworthy or not.

MODUL Technology GmbH will develop in this project the social media data ingestion pipeline. Data ingestion will be driven by in-time news event detection, since at any one time the InVID platform should only be collecting relevant candidate media for the verification process, i.e. videos being posted which claim to show something related to a current news event. Detected events will be appropriately labelled so that a query mechanism which is regularly updated can retrieve candidate media items from the social platforms. These items, in order to allow for user friendly search and browsing in the applications which use the platform data, will be richly annotated according to their content and structure, with a focus on unambiguous entity detection (e.g. for determining the location claimed to be shown in the video). This pipeline will be integrated as part of the InVID project into the webLyzard Web Intelligence Platform, which forms the core of the InVID platform solution.

MODUL Technology’s news event detection and dynamic social media querying components can help drive any organisations data ingestion needs, e.g. for online media monitoring as part of a Marketing Intelligence approach or for social media browsing as part of an UGC re-use strategy on a Website or a social network channel. Let us work it out for you, contact us now!