Yewno provides Augmented Intelligence.

Yewno’s mission is that of extracting knowledge from an overwhelming quantity of unstructured and structured data. Our technology helps to overcome the “information overload” problem and to research and to understand the world in a more natural manner.

It is inspired by the way humans process information from multiple sensorial channels and it leverages state-of-the-art Computational Linguistics, Network Theory, Machine Learning, as well as methods from the classical Artificial Intelligence.


Understanding the nature of knowledge.

At the core of our technology is the framework that extracts, processes, links and represents atomic units of knowledge – concepts – from heterogeneous data sources. A Deep Learning Network continuously “reads” high-quality sources projecting concepts into a multidimensional Conceptual Space where similarity measures along different dimensions are used to group together related concepts. In accord with prominent cognitive theories of conceptual spaces, our space allows for both geometrical, statistical and topological operations, and it permits to aggregate basic concepts into more complex representations.

Thanks to these techniques, a graph-like network, the knowledge graph, is induced and advanced tools from the field of complex networks are utilized to unfold such networks and extract inferences. Yewno’s approach explicitly addresses the temporal evolution of the knowledge network and extracts insights by analyzing not only the nature of the interconnected concepts and communities but also their temporal evolution.