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Technologien aus Wien
detection and prediction of events based on social mediaPrewave is a data-analytics startup and spin-off of the Vienna University of Technology specialized on the prediction of supply chain risks from social media data.
We specialize in turning unstructured text data into structured event data. Our core competency is to develop natural language processing and machine learning algorithms that automatically extract time, place and context information from high volumes of multi-lingual text data and generate event alerts.
Our initial target markets are the supply chain management and corporate sustainability & security markets.
Prewave SCM Predictive AlertsThe goal of this project is to significantly increase the predictive power and the regional coverage of our prediction engine to develop an innovative data product for the supply chain Analytics market. Our prediction engine analyzes high volumes of global social media data and generates alerts when disruptive events are likely to happen. Our target customers are supply chain management leaders and logistics companies, who can improve the efficiency and sustainability of their global supply chains by knowing earlier about potential risks. In this
project, we research, design & develop entirely new natural language processing and machine learning technologies
Using Linked Open Data for Social Media Event PredictionThe goal of this project is to investigate the potential of combining machine learning and semantic web technologies to improve automated event prediction. Existing research in this intersection primarily focused on text data in a single language and news texts. In contrast, Prewave experimentally evaluates linked open data sources and entity linking methods on multi-lingual text social media data. The results are expected to improve event categorization, location extraction and prediction performance.
Kontakt Wirtschaftsagentur Wien
Die Informations- und Vernetzungsangebote werden im Rahmen des Projektes „IC3 Innovation by Co-Operation, Co-Creation and Community Building“ aus Mitteln des Europäischen Fonds für regionale Entwicklung kofinanziert. Nähere Informationen zum IWB/EFRE-Förderprogramm