However, it is precisely this flood of information from the most diverse sources and in different languages that overwhelms the capacity currently in place for reading and analyzing it all and poses major challenges for the economy: if even a simple search query generates several tens of thousands of results just in Google News in German, it is clear that neither companies themselves nor third-party market research partners are in a position to produce a comprehensive evaluation of all relevant published documents and news – even with a very substantial investment in personnel and time. And this challenge is constantly growing in our increasingly digital and volatile world, which demands ever-faster decisions even in the face of swelling volumes of data and information.
Fast and efficient results through new methods for semantic media analysis#
This is why Fraunhofer SCS and the Nuremberg Institute of Technology are working together to develop automated text analysis systems for knowledge generation and trend analysis based on Semantic Web technologies. The aim is to be able to predict market trends and technological developments quickly without impairing their validity.
These new methods make automated trend predictions possible, where large volumes of unstructured texts in various languages sourced from selected websites and databases are scanned by machine and the information found is processed, fleshed out to address relevant questions and placed in the right (corporate) context.
This enables companies to efficiently assess the maturity of technologies and markets, to recognize changes in customer and competitor behavior at an early stage and to transfer industry-specific findings into strategic scenarios.