Models for recognizing categories, entities, roles, and patterns in legal text documents have been developed mainly for forms: They have in common that they require some fixed structure to reliably obtain the relevant information and only predefined subjects are covered by existing algorithms. Neither polystructured nor free text data are interpreted in a meaningful way. Cognitive Services in LegalTech is considered as a platform to handle incoming documents regardless from its format and according to the following aspects: Subdivision and Separation, Categorization, Entity Recognition, and the Anonymization of all personal data, where the assignment of recognized entities to specific roles is the specific complexity that will determine the success of the project in terms of readability and usability. A particular prerequisite for the success of the new approach is also the development of a live quality measure for the quality of the data analysis.
Mag.
Not only because of his statistical background (Master degree in Management Science at WU Wien), Frederick Bednar has been gathered experience as a "data aficionado" for about two decades now.
