Markus is IT and knowledge architect, has more than 3 decades of IT experience and lived through the last two big paradigm shifts from Assembler over structured programming to object-oriented programming.
Having his roots in theoretical physics, he is addicted to simple, shared and expressive modelling, and with his company "die.wissens.in.gen.ieu.re", supports others to make their [first?] semantic steps more successful.
06.01.2015
LOCATION: Basel
KEYWORDS: Meeting, Networking, Lessons learned
AGENDA: | Vortrag und Essen ab 19:00 |
SPEAKER: Markus Pilzecker COMPANY: die.wissens.in.gen.ieu.re
SLIDES: https://www.die.wissens.in.gen.ieu.re/conventus/oratio/2015-01-06.basel.archibale_13/index.html
After we had a coarse theoretical introduction into knowledge engineering with an emphasis on knowledge representation at Archibale 11 in November, our present talk on this topic will refresh, what we have heard, with some practical applications of RDF.
We'll continue with the second major topic of knowledge engineering: knowledge acquisition. Knowledge acquisition deals with extracting meaning from textual material by human language processing methods. A closer look at one of the open-source computer-linguistic analysis tool-chains will give us a rough understanding of its components and which customisations are typically needed to get it running.
The session will be wrapped up by some impressions from the "Semantics 2014" conference, which took place in September in Leipzig. This will give us examples, how others from academia and industry orchestrate the instruments, we have seen, in order to get something practically useful done in this field.
LANGUAGE: Talk: de / Slides: en
Markus is IT and knowledge architect, has more than 3 decades of IT experience and lived through the last two big paradigm shifts from Assembler over structured programming to object-oriented programming.
Having his roots in theoretical physics, he is addicted to simple, shared and expressive modelling, and with his company "die.wissens.in.gen.ieu.re", supports others to make their [first?] semantic steps more successful.
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