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]]. | + | |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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| − | + | 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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Dr. Michael Färber
- Wissenschaftlicher Mitarbeiter
- Tel.:+49 721 608 465 92
- Email: michael faerber∂kit edu
- Raum: 5A-15 (Geb. 05.20)
- Forschungsgruppe: Web Science
- Sprechstunde nach Vereinbarung
- vCard
Neu: offene Hiwi-Stelle im Bereich Text Mining.
Offene, ausgeschriebene Abschlussarbeitsthemen:
| Titel | |
|---|---|
| Thema4420 | Wie fair sind Forscher? Eine Analyse von Zerrungen bzgl. Zitaten in wissenschaftlichen Publikationen |
| Thema4421 | Implementing an Approach for Linking Text to the Knowledge Graph Wikidata |
| Thema4423 | Automatically Recommending Citations for Texts Using Neural Networks |
| Thema4482 | How Do Successful Startups Look Like? Predicting the Success of Startups and Tech Companies |
| Thema4520 | Learning Machine Learning-based Embeddings for Entities, States, and Events |
| Thema4554 | Google, Microsoft, & Co. – How Big is the Influence of Enterprises on Computer Science Research? |
| Thema4574 | Deep Learning + Knowledge Graphs |
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
Abschlussarbeiten
Tools
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 |
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digilog@bw |
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ProData |
Forschungsgebiete
- Semantische Suche, Maschinelles Lernen, Text Mining, Semantische Annotation, Informationsextraktion, Natürliche Sprachverarbeitung, Knowledge Discovery, Künstliche Intelligenz, Data Science, Semantic Web
KIT Funktionen und Kompetenzfelder
Cognition and Information Engineering