Topic: device Learning models utilization for the intent of creating cognition graphs from free text.
Nowadays humans are creating unprecedented amounts of data. A major part of this data is stored in unstructured free text form. In BlackSwan Technologies we are aiming to retrieve information and cognition from those sources. In order to accomplish that we are developing Natural Language Processing models that are converting text (e.g. news article) into a cognition Graph. In our company we besides believe that storing information in cognition Graph form comes with quite a few benefits - especially as an intermediate validation step of our device Learning models and large starting point for gathering insights. Having in place the cognition Graph creation process and insights with visualization tools can be considered as 1 approach to interpretable AI. We would like to show part of the cognition Graph creation process where we incorporate Named Entity designation and relation Extraction models for that purpose.
🔥 [4Developers 2023] https://4developers.org.pl/4developers-2023/
👉 [FB] https://www.facebook.com/4Developers
👉 [LI] https://www.linkedin.com/showcase/4developers
👉 [TT] https://twitter.com/4Developers
