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Information Linking and Retrieval

Information linking develops models which allow for linking heterogenous types of information through semantic web technologies. Information retrieval develops models which improve digital information search.

Main research areas in the field of information linking and retrieval are:

  • User studies and logfile analyses to analyze the information behavior of social scientists
  • Linking different types of information as well as combining survey data with research data from other academic domains
  • Making information retrieval easier and more personal
  • Integrated access to information via linked information (“link retrieval”)
  • Developing domain specific recommender and ranking services
  • Novel logfile based metrics for evaluating interactive retrieval systems

Learn more about our consulting and services:

Name Department Team Email Telephone
Baran, Erdal
Service Strategy & Engineering
Software Engineering
+49 (0221) 47694-511
Bensmann, Felix
Knowledge Technologies for the Social Sciences
Information Extraction and Linking
+49 (0221) 47694-524
Breuer, Dr. Johannes
Computational Social Science
Digital Society Observatory
+49 (0221) 47694-471
Culbert, John
Knowledge Technologies for the Social Sciences
Information and Data Retrieval
+49 (0221) 47694-731
Dahou, Abdelhalim Hafedh
Knowledge Technologies for the Social Sciences
FAIR Data
+49 (0221) 47694-430
Dimitrov, Dr. Dimitar
Knowledge Technologies for the Social Sciences
Information Extraction and Linking
+49 (0221) 47694-512
Hienert, Dr. Daniel
Knowledge Technologies for the Social Sciences
Information and Data Retrieval
+49 (0221) 47694-525
Kampmann, Jara (M. Sc.)
Data Services for the Social Sciences
Data Acquisitions and Access
+49 (0221) 47694-456
Kern, Dr. Dagmar
Knowledge Technologies for the Social Sciences
Human Information Interaction
+49 (0221) 47694-536
Krämer, Thomas
Knowledge Technologies for the Social Sciences
Human Information Interaction
+49 (0221) 47694-201
Mayr, Dr. Philipp
Knowledge Technologies for the Social Sciences
Information and Data Retrieval
+49 (0221) 47694-533
Momeni, Fakhri
Knowledge Technologies for the Social Sciences
Human Information Interaction
+49 (0221) 47694-544
Mutschke, Peter (M.A.)
Knowledge Technologies for the Social Sciences
FAIR Data
+49 (0221) 47694-500
Otto, Wolfgang
Knowledge Technologies for the Social Sciences
Information Extraction and Linking
+49 (0221) 47694-543
Soldner, Felix
Computational Social Science
Digital Society Observatory
+49 (0221) 47694-234
Tavakolpoursaleh, Narges
Knowledge Technologies for the Social Sciences
Data and Services Engineering
+49 (0221) 47694-140
Zloch, Dr. (rer. nat.) Matthäus
+49 (0221) 47694-534
  • Dahou, Abdelhalim Hafedh, Mohamed Amine Cheragui, and Ahmed Abdelali. 2023. "Performance Analysis of Arabic Pre-Trained Models on Named Entity Recognition Task." In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, edited by Ruslan Mitkov, and Galia Angelova, 458–467. Shoumen: INCOMA Ltd.. https://aclanthology.org/2023.ranlp-1.51.pdf.
  • Diera, Andor, Abdelhalim Hafedh Dahou, Lukas Galke, Fabian Karl, Florian Sihler, and Ansgar Scherp. 2023. GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding. Proceedings of the 1st GenBench Workshop on (Benchmarking) Generalisation in NLP. Association for Computational Linguistics (ACL). doi: https://doi.org/10.18653/v1/2023.genbench-1.2.
  • Dahou, Abdelhalim Hafedh, and Brigitte Mathiak. 2023. "Subject Classification of Software Repository." In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR, 1, 30-38. SciTePress. doi: https://doi.org/10.5220/0012159600003598.
  • Dahou, Abdelhalim Hafedh, and Mohamed Amine Cheragui. 2023. "DzNER: A large Algerian named entity recognition dataset." Natural Language Processing Journal 3 (June 2023): 100005. doi: https://doi.org/10.1016/j.nlp.2023.100005.
  • Dahou, Abdelhalim Hafedh. 2021. "A3C: Arabic Anaphora Annotated Corpus." Proceedings of the 4th International Conference on Natural Language and Speech Processing (ICNLSP 2021), 147–155. Association for Computational Linguistics.