17:30 - 21:00
A1 Telekom Austria
Lassallestraße 9, 1020 - Wien
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 Intoduction (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)
Open Knowledge Maps: how to increase visibility of research findings using NLP, Semantics, Open Data and Community
- 18:45 Rene Donner (Contextflow)
Large Scale Medical Image Retrieval at contextflow
- 19:00 Lightning Talks, DMA Incubator Program, Networking
- Christian Blaschke (Semantic Web Company) The Semantic Layer for contextualising industrial process data.
- Sabrina Kirrane (WU Executive Academy) From Data Analyst to Data Scientist
- Peter Tschuchnig (INiTS) The DMA Incubator Programme
This is a joint Meetup of the Vienna Data Science Group, the Data Market Austria and the Vienna Semantic Web Meetup