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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. Source


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. Source


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 ...


Grant
Agency: Cordis | 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.


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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