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Visit us on the 23rd of May in Vienna and experience why machines learn better with semantics!

Semantic Web and Data Science are complementary disciplines working on solving problems based on large amounts of data. While Semantic Web technologies are based on Symbolic AI, Data Science relies rather on statistics and applies statistical approaches to AI.

Both disciplines approach same challenges from different perspectives while related to extracting meaningful information from several sources and large amounts of data. How to put those approaches together in a way that decision-makers could use it?

In this Meetup, we will present recent developments at the intersection of machine learning and semantic knowledge modelling. We will discuss practical use case scenarios to illustrate potential results that could be achieved through the collaboration between both fields.


17:30 Welcome and Introduction (VSWM, VDSG, DMA)
17:45 Andreas Blumauer (Semantic Web Company)
Semantic enhanced Artificial Intelligence
18:00 Break
18:15 Xander Wilcke (Vrije Universiteit Amsterdam)
The Knowledge Graph for End-to-End Learning on Heterogeneous Knowledge
18:30 Peter Kraker (Open Knowledge Maps)
Title to be defined
18:45 Georg Langs (Contextflow)
Title to be defined
19:00 Lightning Talks, DMA Incubator Program, Networking

This is a joint Meetup of the Vienna Data Science Group, the Data Market Austria and the Vienna Semantic Web Meetup.

Take a look at the website