The ongoing digital transformation is driving a rapid increase in the volume of available text-based data, and this growth is accelerating steadily. It is therefore no easy task to organize, process, and analyze this overwhelming amount of information and data.
We offer sophisticated natural language processing (NLP) software solutions as an effective tool for the automated processing of natural language texts. This technology holds great potential for making business processes more efficient, resource-efficient, and cost-effective. The core technical component is what are known as language models, which are also available in multilingual versions.
When unstructured data repositories make it difficult to find relevant information, and specifying precise keywords in a search query is practically impossible or undesirable, NLP language models (e.g., as an additional search option) can enable a flexible search that compares the meaning of the search query with the information in the data repository and presents the results that are semantically most similar to the search query. Furthermore, the language models can be adapted to domain-specific language.
NLP methods can automatically analyze and review natural language text and prepare it for subsequent processing steps. In addition, it is possible to associate instances or information with a text based on its meaning—for example, assigning the responsible department to a customer inquiry or linking relevant legal texts to a described situation. By automating repetitive tasks, this allows employees to focus on their core competencies.
If daily business processes generate large amounts of text-based data, and if—depending on the processing workflows—only a certain portion of that data is relevant, language models can be trained to automatically extract the relevant information.
Another typical NLP application enables the automatic translation of text-based data from one language to another.
The goal of the project is to reliably and automatically translate natural-language requirements for technical systems into a machine-readable format. Various NLP tools—including open-source systems with OHB Digital Services serving as the knowledge provider—will be applied to natural-language requirements from real-world space projects. The project is funded by the Federal Ministry for Economic Affairs and Climate Action as part of the National Program for Space and Innovation and receives technical and administrative support from the German Space Agency at the DLR.
At the heart of this research project is a domain-specific semantic search engine that, in the context of aerospace-related requirements documents, takes into account the meaning of individual words in a text—unlike conventional keyword-based search. This modular software solution thus enables users to search for documents and specific information without having to rely on specific keywords. As a result, employees can find the documents they need without having to rely on expert knowledge and do not have to search through (unstructured) data repositories.
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