webLyzard technology gmbh

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Scharl A.,MODUL University Vienna | Scharl A.,webLyzard technology gmbh | Herring D.,National Oceanic and Atmospheric Administration | Rafelsberger W.,webLyzard technology gmbh | And 5 more authors.
IEEE Systems Journal | Year: 2017

Given the intense attention that environmental topics such as climate change attract in news and social media coverage, scientists and communication professionals want to know how different stakeholders perceive observable threats and policy options, how specific media channels react to new insights, and how journalists present scientific knowledge to the public. This paper investigates the potential of semantic technologies to address these questions. After summarizing methods to extract and disambiguate context information, we present visualization techniques to explore the lexical, geospatial, and relational context of topics and entities referenced in these repositories. The examples stem from the Media Watch on Climate Change, the Climate Resilience Toolkit and the NOAA Media Watch - three applications that aggregate environmental resources from a wide range of online sources. These systems not only show the value of providing comprehensive information to the public, but also have helped to develop a novel communication success metric that goes beyond bipolar assessments of sentiment. © 2016 IEEE.

Agency: European Commission | Branch: FP7 | Program: CP | Phase: ICT-2013.4.2 | Award Amount: 3.64M | Year: 2014

This project proposes a unified, open-source execution framework for scalable data analytics. Data analytics tools have become essential for harnessing the power of our eras data deluge. Current technologies are restrictive, as their efficacy is usually bound to a single data and compute model, often depending on proprietary systems. The main idea behind ASAP is that no single execution model is suitable for all types of tasks and no single data model (and store) is suitable for all types of data. The project makes the following innovative contributions:\n\n(a) A general-purpose task-parallel programming model. The runtime will incorporate and advance state-of-the-art task-parallel programming models features, namely: (i) irregular general-purpose computations, (ii) resource elasticity, (iii) synchronization, data-transfer, locality and scheduling abstraction, (iv) ability to handle large sets of irregular distributed data, and (v) fault-tolerance.\n\n(b) A modeling framework that constantly evaluates the cost, quality and performance of data and computational resources in order to decide on the most advantageous store, indexing and execution pattern available.\n\n(c) A unique adaptation methodology that will enable the analytics expert to amend the task she has submitted at an initial or later stage.\n\n(d) A state-of-the-art visualization engine that will enable the analytics expert to obtain accurate, intuitive results of the analytics tasks she has initiated in real-time.\n\nTwo exemplary applications that showcase the ASAP technology in the areas of Web content and large-scale business analytics will be developed. The consortium -- led by the Foundation for Research & Technology -- is well-positioned to achieve its objectives by bringing together a team of leading researchers in data-management technologies. These are combined with active industrial and leading user organizations that offer expertise in the production-level domain of data analytics.

Agency: European Commission | Branch: H2020 | Program: IA | Phase: ICT-19-2015 | Award Amount: 3.77M | Year: 2016

In video veritas, if we divert the old Latin saying: In video, there is truth! The digital media revolution and the convergence of social media with broadband wired and wireless connectivity are bringing breaking news to online video platforms; and, news organisations delivering information by Web streams and TV broadcast often rely on user-generated recordings of breaking and developing news events shared by social media to illustrate the story. However, in video there is also deception. Access to increasingly sophisticated editing and content management tools, and the ease in which fake information spreads in electronic networks requires reputable news outlets to carefully verify third-party content before publishing it, reducing their ability to break news quickly while increasing costs in times of tight budgets. InVID will build a platform providing services to detect, authenticate and check the reliability and accuracy of newsworthy video files and video content spread via social media. This platform will enable novel newsroom applications for broadcasters, news agencies, web pure-players, newspapers and publishers to integrate social media content into their news output without struggling to know if they can trust the material or how they can reach the user to ask permission for re-use. It will ensure that verified and rights-cleared video content is readily available for integration into breaking and developing news reports. Validated by real customer pilots, InVID will help protecting the news industry from distributing fakes, falsehoods, lost reputation and ... lawsuits. The InVID platform and applications will be validated and qualified through several development and validation cycles. They will be pilot-tested by three leading institutions in the European news industry ecosystem: AFP (the French News Agency), DW (Deutsche Welle), and APA (the Austria Press Agency), and will create new exploitation possibilities for all consortium members.

Weichselbraun A.,Vienna University of Economics and Business | Wohlgenannt G.,webLyzard technology gmbh | Scharl A.,MODUL University Vienna
Proceedings of the Annual Hawaii International Conference on System Sciences | Year: 2011

Recent research shows the potential of utilizing data collected through Web 2.0 applications to capture domain evolution. Relying on external data sources, however, often introduces delays due to the time spent retrieving data from these sources. The method introduced in this paper streamlines the data acquisition process by applying optimal stopping theory. An extensive evaluation demonstrates how such an optimization improves the processing speed of an ontology refinement component which uses Delicious to refine ontologies constructed from unstructured textual data while having no significant impact on the quality of the refinement process. Domain experts compare the results retrieved from optimal stopping with data obtained from standardized techniques to assess the effect of optimal stopping on data quality and the created domain ontology. © 2011 IEEE.

Scharl A.,MODUL University Vienna | Weichselbraun A.,webLyzard technology gmbh | Gobel M.,Vienna University of Economics and Business | Rafelsberger W.,webLyzard technology gmbh | Kamolov R.,MODUL University Vienna
Proceedings of the Annual Hawaii International Conference on System Sciences | Year: 2016

Understanding stakeholder perceptions and assessing the impact of campaigns are key questions of communication experts. Web intelligence platforms help to answer such questions, provided that they are scalable enough to analyze and visualize information flows from volatile online sources in real time. This paper presents a distributed architecture for aggregating Web content repositories from Web sites and social media streams, memory-efficient methods to extract factual and affective knowledge, and interactive visualization techniques to explore the extracted knowledge. The presented examples stem from the Media Watch on Climate Change, a public Web portal that aggregates environmental content from a range of online sources. © 2016 IEEE.

Nixon L.,MODUL University Vienna | Bauer M.,MODUL University Vienna | Scharl A.,MODUL University Vienna | Scharl A.,webLyzard technology gmbh
CEUR Workshop Proceedings | Year: 2014

This demo will show work to enhance a Web intelligence platform which crawls and analyses online news and social media content about climate change topics to uncover sentiment and opinions around those topics over time to also incorporate the content within non-textual media, in our case YouTube videos. YouTube contains a lot of organisational and individual opinion about climate change which currently can not be taken into account by the platforms sentiment and opinion mining technology. We describe the approach taken to extract and include the content of YouTube videos and why we believe this can lead to improved Web intelligence capabilities.

webLyzard technology gmbh | Entity website

The United Nations Environment Programme (UNEP) has chosen the webLyzard platform to build a pioneering Web intelligence solution for global environmental indicators and related communication flows. The platform helps stakeholders to meet environmental goals and foster sustainable development ...

webLyzard technology gmbh | Entity website

The importance of storytelling in marketing communications is not only reflected in the interactive visualizations of the webLyzard dashboard, but also in its analytic services and success metrics. Positive versus negative sentiment reflects the popularity of a brand, organization, or topic ...

webLyzard technology gmbh | Entity website

webLyzard captures and analyzes large amounts of digital content from many different stakeholders millions of documents and user comments from news media, blogs, Web 2.0 platforms (Twitter, Facebook, Google+, YouTube), Fortune 1000, NGO Web sites, and customized samples including competitors, clients and partner organizations ...

webLyzard technology gmbh | Entity website

Communications Manager and Product Evangelist Media Analytics and Web Intelligence Full- or part-time position in Vienna, Austria Position Announcement (PDF, 1.5 mb) Do you have a passion for engaging user experiences and novel solutions to challenging technical problems? We seek outstanding candidates with strong communication skills for telling our story to the market, focusing on webLyzards award-winning media analytics and Web intelligence platform ...

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