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Michael Färber: Unterschied zwischen den Versionen

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* Data Science
 
* Data Science
 
gerne willkommen.
 
gerne willkommen.
|Info EN=New: [[Media:HiWi-Ausschreibung_BMW_2019.pdf|Call for a student job in the area of text mining]].
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|Info EN=<br>Short bio:</b> Michael Färber is a postdoctoral researcher in Prof. Dr. York Sure-Vetter's Web Science group at the Institute AIFB of the Karlsruhe Institute of Technology (KIT), Germany, since April 2019. From 2017 until March 2019, Michael worked in Prof. Dr. Georg Lausen's group at the University of Freiburg, Germany, and at Kyoto University, Japan, as JSPS fellow. From 2012 until 2017, Michael was a PhD student and research associate in Prof. Dr. Rudi Studer's group "Knowledge Management and Web Science" at the Institute AIFB of the Karlsruhe Institute of Technology (KIT), Germany. The title of his PhD thesis is "Semantic Search of Novel Information." Michael's research interests are in natural language processing, machine learning, and the semantic web. He has served as reviewer and PC member for various conferences and journals, including AAAI, ECMLPKDD, IJCAI, ISWC, JWS, and SWJ.
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New: [[Media:HiWi-Ausschreibung_BMW_2019.pdf|Call for a student job in the area of text mining]].
  
 
Calls for Bachelor/Master thesis:
 
Calls for Bachelor/Master thesis:
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| ?Titel
 
| ?Titel
 
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(see English description)
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All topics are open to English and German speaking students.
 
|KIT Kompetenzfeld1=Cognition and Information Engineering
 
|KIT Kompetenzfeld1=Cognition and Information Engineering
 
|Publikationen anzeigen=Ja
 
|Publikationen anzeigen=Ja

Version vom 6. Juli 2019, 20:02 Uhr

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Neu: offene Hiwi-Stelle im Bereich Text Mining.

Offene, ausgeschriebene Abschlussarbeitsthemen:

 Titel
Thema4420Wie fair sind Forscher? Eine Analyse von Zerrungen bzgl. Zitaten in wissenschaftlichen Publikationen
Thema4421Implementing an Approach for Linking Text to the Knowledge Graph Wikidata
Thema4423Automatically Recommending Citations for Texts Using Neural Networks
Thema4574Deep Learning + Knowledge Graphs
Thema4771Analyzing the Influence of Enterprises and Countries on AI Research
Thema4772GPT-3, BERT & Co.: When to use which language model?

Anfragen zu weiteren Abschlussarbeitsthemen zu Themen wie

  • Natural Language Processing (NLP) / Text Mining
  • Angewandtes Machine Learning
  • Semantic Web / Linked Data
  • Big Data
  • Data Science

gerne willkommen.


Publikationen
Publikationen


Vorträge
Vorträge


Abschlussarbeiten
Abschlussarbeiten


Tools

FAIRnets, KB-Statistics, Linked Crunchbase, Novel Triple Extraction


Datasets

CrunchBase Knowledge Graph, KORE 50^DYWC, Microsoft Academic Knowledge Graph, NewsBias2020, UnarXive, XLiD-Lexica


Aktive Projekte
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AI in Peacemaking
Externer Link: https://mediatingmachines.com/

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DataScore
Externer Link: https://datascore.int.kit.edu/

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digilog@bw
Externer Link: https://digilog-bw.de

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KIGLIS

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ProData
Externer Link: http://www.pro-data.org

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TransPer





Forschungsgebiete
Semantische Suche, Wissensrepräsentation, Maschinelles Lernen, Text Mining, Semantische Annotation, Informationsextraktion, Natürliche Sprachverarbeitung, Digitale Bibliotheken, Knowledge Discovery, Data Mining, Künstliche Intelligenz, Data Science, Semantic Web, Trustworthy AI


KIT Funktionen und Kompetenzfelder

Cognition and Information Engineering