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* [http://www.aifb.kit.edu/web/Michael_F%C3%A4rber2 Abstract of Michael Färber's AIFB Colloquium talk about his PhD topic]
 
<br />
 
* '''Supervised Bachelor/Master Theses:'''
 
 
<table id="tg-3U7C5">
 
  <tr>
 
    <th>Student Name</th>
 
    <th>Title</th>
 
    <th>Kind of Thesis</th>
 
    <th>Submission Date</th>
 
  </tr>
 
  <tr>
 
    <td>Samuel Printz</td>
 
    <td>Text Annotation with Wikidata</td>
 
    <td>Bachelor</td>
 
    <td>ongoing</td>
 
  </tr>
 
  <tr>
 
    <td>Johannes Reiss</td>
 
    <td>A Probabilistic Model for Predicting Wikipedia Pages</td>
 
    <td>Master</td>
 
    <td>ongoing</td>
 
  </tr>
 
  <tr>
 
    <td>Laurenz Vorderwülbecke</td>
 
    <td>Rule-based Noun Phrase Extraction Using Part-of-Speech Tags</td>
 
    <td>Bachelor</td>
 
    <td>2016</td>
 
  </tr>
 
  <tr>
 
    <td>Felix Drabe</td>
 
    <td>Automatically Determining Text Quality</td>
 
    <td>Master</td>
 
    <td>ongoing</td>
 
  </tr>
 
  <tr>
 
    <td>Zihan Lin</td>
 
    <td>Feature Selection for Predicting the Creation of New Wikipedia Articles</td>
 
    <td>Bachelor</td>
 
    <td>2016</td>
 
  </tr>
 
  <tr>
 
    <td>Chris Konop</td>
 
    <td>Finding Events in Unstructured Text</td>
 
    <td>Bachelor</td>
 
    <td>2016</td>
 
  </tr>
 
  <tr>
 
    <td>Frederic Bartscherer</td>
 
    <td>Linked Data Quality: A Comparison of DBpedia, YAGO, Freebase, Wikidata and OpenCyc</td>
 
    <td>Master</td>
 
    <td>2016</td>
 
  </tr>
 
  <tr>
 
    <td>Steffen Strobl</td>
 
    <td>Trend Detection: Predicting the Emergence of Wikipedia Articles</td>
 
    <td>Bachelor</td>
 
    <td>2015</td>
 
  </tr>
 
  <tr>
 
    <td>Peter Natterer</td>
 
    <td>Detecting Emerging Entities based on News Texts</td>
 
    <td>Master</td>
 
    <td>2016</td>
 
  </tr>
 
  <tr>
 
    <td>Moritz Winckler</td>
 
    <td>Knowledge Base Enrichment from OpenIE Input</td>
 
    <td>Bachelor</td>
 
    <td>2015</td>
 
  </tr>
 
  <tr>
 
    <td>Bo Liu</td>
 
    <td>Automatically Adding References to Text</td>
 
    <td>Bachelor</td>
 
    <td>2015</td>
 
  </tr>
 
  <tr>
 
    <td>Johannes Spohr</td>
 
    <td>Evaluation of Performance Gain of Semantic Search for Experienced Users and Novices</td>
 
    <td>Master</td>
 
    <td>2015</td>
 
  </tr>
 
  <tr>
 
    <td>Chunyan Zhong</td>
 
    <td>Machine Learning Methods for Dealing with Errors and Incomplete Records</td>
 
    <td>Master</td>
 
    <td>2015</td>
 
  </tr>
 
  <tr>
 
    <td>Alexander Kraetke</td>
 
    <td>Analysis of Wikidata and Usage for Semantic Search</td>
 
    <td>Master</td>
 
    <td>2015</td>
 
  </tr>
 
  <tr>
 
    <td>Swetlana Stickhof</td>
 
    <td>Named Entity Recognition for Improving Entity Linking with Wikipedia and Detecting New Named Entities in Text Documents</td>
 
    <td>Bachelor</td>
 
    <td>2014</td>
 
  </tr>
 
  <tr>
 
    <td>Wojtek Breiter</td>
 
    <td>Access Control in Semantic MediaWiki</td>
 
    <td>Diploma</td>
 
    <td>2014</td>
 
  </tr>
 
  <tr>
 
    <td>Frederic Engelen</td>
 
    <td>Implementation of a User Interface for Visualizing New Facts Found in Text Documents</td>
 
    <td>Bachelor</td>
 
    <td>2014</td>
 
  </tr>
 
  <tr>
 
    <td>David Kleinmann</td>
 
    <td>Identification of Statements in Unknown Texts via SRL Graphs and Machine Learning Methods</td>
 
    <td>Bachelor</td>
 
    <td>2014</td>
 
  </tr>
 
  <tr>
 
    <td>Waldemar Koller</td>
 
    <td>Relation Extraction With the Help of Machine Learning Methods</td>
 
    <td>Master</td>
 
    <td>2014</td>
 
  </tr>
 
  <tr>
 
    <td>Wolf Quaschningk</td>
 
    <td>Technology Portfolios and Technology Roadmaps in Semantic Wikis</td>
 
    <td>Diploma</td>
 
    <td>2014</td>
 
  </tr>
 
  <tr>
 
    <td>Georg Ertl</td>
 
    <td>Neural Networks for Predicting the Energy Production of Hydroelectric Power Stations</td>
 
    <td>Master</td>
 
    <td>2014</td>
 
  </tr>
 
  <tr>
 
    <td>Philipp Kuepper</td>
 
    <td>Potential of Knowledge Management in Procurement</td>
 
    <td>Master</td>
 
    <td>2013</td>
 
  </tr>
 
</table>
 
<br />
 
* '''Reviewer/Subreviewer for'''
 
** AAAI Conference on Artificial Intelligence (AAAI)
 
** Asian Conference on Machine Learning (ACML)
 
** European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD)
 
** Extended Semantic Web Conference (ESWC)
 
** IEEE/WIC/ACM International Conference on Web Intelligence (WI)
 
** International Conference on Knowledge Capture (K-CAP)
 
** International Conference on Knowledge Engineering and Knowledge Management (EKAW)
 
** International Conference on Semantic Systems (SEMANTiCS)
 
** International Conference on Web Information Systems and Technologies (WebIST)
 
** International Joint Conference on Artificial Intelligence (IJCAI)
 
** International Semantic Web Conference (ISWC)
 
** Journal of Web Semantics (JWS)
 
** Modeling, Learning and Mining for Cross/Multilinguality Workshop (MultiLingMine)
 
** Semantic Web Journal (SWJ)
 
<br />
 
 
* '''Online Demos'''
 
** Wikipedia Article Recommender
 
**:http://km.aifb.kit.edu/services/wikipedia-recommender (online January 2017)
 
**:Michael Färber, Achim Rettinger, Boulos El Asmar: On Emerging Entity Detection, 20th International Conference on Knowledge Engineering and Knowledge Management (EKAW’16), Bolognia, Italy, November, 2016.
 
 
** Rule-based Base Noun Phrase Extractor
 
**:http://km.aifb.kit.edu/services/np-extractor (online end of December 2016 online)
 
**:not yet published
 
 
**CrunchBase RDF Wrapper
 
**:http://km.aifb.kit.edu/services/crunchbase
 
**:Michael Färber, Carsten Menne, Andreas Harth: A Linked Data Wrapper for CrunchBase, Semantic Web Journal, 2016 (under review, available at http://www.semantic-web-journal.net/content/linked-data-wrapper-crunchbase-1; journal impact factor: 1.786)
 
 
**XKnowSearch!
 
**:http://km.aifb.kit.edu/services/XKnowSearch
 
**:Lei Zhang, Michael Färber, Achim Rettinger: XKnowSearch! Exploiting Knowledge Bases for Entity-based Cross-lingual Information Retrieval, The 25th ACM International on Conference on Information and Knowledge Management (CIKM’ 2016), Indianapolis, IN, USA, October, 2016.
 
 
** DBpedia Successors
 
**:http://km.aifb.kit.edu/services/dbpedia-successors
 
**:not yet published
 
 
** Kuphi
 
**:http://km.aifb.kit.edu/services/kuphi
 
**:Michael Färber, Lei Zhang, Achim Rettinger: Kuphi - An Investigation Tool for Searching for and via Semantic Relations. In The Semantic Web: ESWC 2014 Satellite Events, Volume 8798 of the series Lecture Notes in Computer Science, pp. 349-354, 2014.
 
 
** Further source code online at http://people.aifb.kit.edu/mfa/projects/synctech/
 

Aktuelle Version vom 2. März 2020, 19:55 Uhr

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Michael Färber is the deputy professor (W3) of the research group Web Science at the KIT-institute AIFB since October 2020. He is also a Helmholtz AI Associate.

News:

  • Seminar/Internship on ChatGPT in March 2023 -- apply now as Master or Bachelor student!
  • Exp. Feb 02 -- Mar 31, 2023: Research stay at the NII (Tokyo)
  • Oct 27, 2022: Best Poster award (300 USD) for The Green AI Ontology at ISWC'22.
  • Aug 01 -- Sep 30, 2022: Research stay/guest professorship at the Digital Science Center (DiSC), University of Innsbruck.
  • Jul 12, 2022: NAACL Paper: Few-Shot Document-Level Relation Extraction


Michael Färber on


Research

Profile: As W3 Deputy Full Professor until 2025, I am the head of the research group Web Science at the Karlsruhe Institute of Technology (KIT). Together with my team of seven PhD students and one postdoc, I work on the development and application of artificial intelligence (AI) methods. Specifically, my focus is in the triangle of knowledge representation, machine learning, and natural language processing. Since my postdoc phase, my vision is to work on solutions for the increasing scholarly information overload and on new ways of scholarly communication. To this end, I perform research on extracting and modeling scientific knowledge explicitly in the form of scholarly knowledge graphs, and develop search and recommender systems that leverage the explicitly modeled scholarly knowledge, while being able to explain the results and recommendations to the user. I have published more than 75 publications at prestigious international conferences (e.g., CIKM, ISWC, ECIR, NAACL) with international researchers. Furthermore, I contribute as PI to several projects (e.g., KD4RE, IIDI, ChemKB, KIGLIS, digilog@bw).


publications

Research Interests

  • natural language processing,
  • machine learning, and
  • knowledge representation (e.g., knowledge graphs).


Among other things, Michael Färber pursues research on scholarly data mining (e.g., scientific impact quantification), scholarly recommender systems (e.g., recommending citations, papers, data sets, and neural networks), and scholarly knowledge graphs (e.g., modeling papers, authors, methods, and datasets). Furthermore, he develops AI solutions for peace mediation (see AI4Peace).

More information can be found at his homepage and on Google Scholar.

Online Demo Systems

Recently developed demonstration systems:

  • RefBee: http://refbee.org/
    • ...shows for an author which publications are in which bibliographic databases.
  • C-Rex: http://c-rex.org
    • ... recommends citations for given texts.
  • PaperHunter: http://paperhunter.net
    • ... provides, among other things, the sentences in which searched papers are cited.
  • ScholarSight: http://scholarsight.org
    • ... allows the exploration of trends from scientific concepts.
  • Linked Crunchbase: http://linked-crunchbase.org
    • ... allows to query information about startups and innovative companies in the Semantic Web format RDF.


Data Sets

Recently created data sets:

  • DSKG: http://dskg.org
    • ...a knowledge graph representing datasets.
  • unarXive: http://unarxive.org
    • ... contains the full texts of all papers on arXive.org with further annotations.
  • Microsoft Academic Knowledge Graph: https://makg.org
    • ... a knowledge graph containing the metadata of almost all publications in all scientific disciplines.
  • FAIRnets: https://doi.org/10.5281/zenodo.3885249
    • ...a knowledge graph with metadata about neural networks.


Code, Data, and Presentations



Open Positions and Theses

Open student assistant jobs (Hiwis)

  • in machine learning, natural language processing, or knowledge graphs: [1]
  • in Semantic MediaWiki or PHP: [2].


Current calls for Bachelor/Master thesis

 Titel
Thema4977Knowledge Graphs for Robots’ Situational Awareness
Thema4939Chronik 2050: Automatische Extraktion von erwarteten Ereignissen aus Webseiten
Thema4864Quantum Computing for Natural Language Processing
Thema4420Wie fair sind Forscher? Eine Analyse von Zerrungen bzgl. Zitaten in wissenschaftlichen Publikationen
Thema4909Scalable Graph Neural Networks on Knowledge Graphs
Thema4910Performance Analysis of Graph Neural Diffusion via Fourier Decomposition
Thema4648Creating a Large Knowledge Graph about Scientific Publications for Innovation Forecast
Thema4574Deep Learning + Knowledge Graphs
Thema4772GPT-3, BERT & Co.: When to use which language model?
Thema4423Automatically Recommending Citations for Texts Using Neural Networks

I have supervised more than 50 Bachelor/Master theses (➜ List of all completed theses directly supervised).
All topics are open to English and German-speaking students.

Theses Abroad

Many of the thesis topics can also be written at a partner institution abroad (e.g. in Japan, USA) and funded by the DAAD. More information under Web_Science/DAAD-Stipendium/en.



Publications
Publications


Active Projects
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ChemKB

Digilog-logo.png

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

IIDI Logo.png

IIDI

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KD4RE

Kiglis logo.png

KIGLIS
External Link: http://www.kiglis.de/


Research area
Semantic Search, Knowledge Representation And Reasoning, Machine Learning, Text Mining, Semantical Annotation, Information Extraction, Natural Language Processing, Digital Libraries, Knowledge Discovery, Data Mining, Artificial Intelligence, Data Science, Semantic Web, Trustworthy AI