Research, projects & publications

The AI-based Natural Language Processing of Low-Quality and Multilingual Data in Defence Applications with Self-Adaptation (AtLaS) project aims to revolutionize Human Language Technology (HLT) in Defence applications. Spearheaded by a diverse European consortium, AtLaS develops advanced HLTs for challenging Defence contexts, ensuring robust communication and seamless information processing. AtLaS focuses on creating resilient systems that withstand noise and handle multiple languages. Utilizing cutting-edge technologies like denoising and integrating neural networks with semantic knowledge, AtLaS creates solutions for effective communication in diverse Defence scenarios.

Knowledge graphs (KGs) are a flexible knowledge representation paradigm intended to allow knowledge to be consumed by humans and machines. KGs are widely regarded as a key enabler for a number of increasingly popular technologies including Web search, question answering, personal assistants and AI across most sectors including Industry 4.0, personalized medicine, legislation, economics and more. KGs are now used by several large companies as a key component of their data products. However, while they are rightly praised as a key technology for all future data-driven enterprises and regarded as a promising approach towards “blurring the lines between human and machine”, KGs are currently unattainable for the majority of companies and users.