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Corporate Semantic Web

The proseminar/seminar will focus on semantic technologies, (Corporate) Semantic Web, artificial intelligence (AI) and declarative knowledge representation in the enterprise context.

(19318517)

TypeSeminar
InstructorAdrian Paschke
StartApr 22, 2020
endJul 18, 2020
Time

10:15 - 11:45

Zeitraum: 22.4.2020 bis 18.7.2020


Termin Thema Referent
22.4. Einführung  Adrian Paschke
 6.5.  Künstliche Intelligenz und Cognitive Computing  Dastan Kasmamytov
 6.5.  Semantic Web und semantische Technologien / Standards  Kaan Dönmez
 13.5.  Engineering Ontologies  Tjard Hoffmann
 13.5.  Knowledge graphs, DBPedia (incl. Linked Open Data), Yago, Wikidata  Emil Merle
 20.5.  Topic detection  Boyan Hristov
 27.5.  Entity Linking and Knowledge Extraction  Raphael Taxis
 3.6.  Relation extraction and classification using deep learning  Petrit Vidishiqi
 3.6.  Ontology Learning  Fritz Pilz
 10.6.  Stream Reasoing  Elana Frank
 17.6.  Question answering with deep learning  Benny Henning
 17.6.  Quantum Machine Learning  Jan Batelka
 24.6.  Explainable AI  Mamon Dehabra
 24.6.  Neural-symbolic learning and reasoning  Friedrich Keinhorst
 1.7.  Abschluss  Adrian Paschke


Templates für Präsentation und Seminararbeit

Template Seminararbeit (im KVV )

Template Präsentation (im KVV )

 

Ablauf und Leistungserbringung

Das Seminar findet online statt. Zugangsdaten im KVV.

siehe http://www.ag-nbi.de/lehre/seminare.html

Bitte beachten Sie auch die Hinweise zu Plagiaten.

 

Themen

  1. Künstliche Intelligenz und Cognitive Computing (Dastan Kasmamytov)
  2. Logik Programmierung und Regeln
  3. Beschreibungslogiken / Description Logics
  4. Semantic Web und semantische Technologien / Standards (Kaan Dönmez)
  5. Engineering Ontologies (Tjard Hoffmann)
  6. Named Entity Recognition (NER): Grundlagen, State of the Art, Tools (Amr Dargham)
  7. Knowledge graphs, DBPedia (incl. Linked Open Data), Yago, Wikidata (Emil Merle)
  8. Topic detection (Boyan Hristov)
  9. (Semantic) Business Process Modelling
  10. Semantische Recommender Systeme
  11. Entity Linking and Knowledge Extraction („The Open Knowledge Extraction Challenge) (Raphael Taxis)
  12. Semantic Search (Tim Kluge)
  13. Corporate Semantic Web Applications (Semantic CMS/KMS/DMS/Wiki)
  14. Stream Reasoing (Elana Frank)
  15. Inductive Logic Programming
  16. Rule Extraction and Rule Learning
  17. Ontology Learning (Fritz Pilz)
  18. Deep learning and structured knowledge / logic rules
  19. Deep learning for time-series modeling
  20. Relation extraction and classification using deep learning (Petrit Vidishiqi)
  21. Knowledge base population using deep learning
  22. Question answering with deep learning (Benny Henning)
  23. Neural-symbolic learning and reasoning (Friedrich Keinhorst)
  24. Explainable AI (Mamon Dehabra)
  25. Quantum Machine Learning (Jan Batelka)
  26. + further topics (suggest one)