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.

Our research on Information Linking and Retrieval

  • 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
  • Bensmann, Felix, and Benjamin Zapilko. 2023. ScienceLinker - Python Package. https://pypi.org/project/sciencelinker/.
  • Dahou, Abdelhalim Hafedh, and Brigitte Mathiak. 2024 (Forthcoming). "Automatic Categorization of Software Repository Domains with Minimal Resources."
  • 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.

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