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
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- Kroneberg, Clemens, Sven Lenkewitz, André Ernst, Maike Meyer, and Kai Seidensticker. 2022. "Using police data to measure criminogenic exposure in residential and school contexts: experiences from a data linkage project in Germany." Police Practice and Research 23 (4): 473-488. doi: https://doi.org/10.1080/15614263.2022.2046569.
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- Carevic, Zeljko, Dwaipayan Roy, and Philipp Mayr. 2020. "Characteristics of dataset retrieval sessions: Experiences from a real-life digital library." In Digital Libraries for Open Knowledge : 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, Lyon, France, August 25–27, 2020, Proceedings, edited by Mark Hall, Tanja Merčun, Thomas Risse, and Fabien Duchateau, Lecture Notes in Computer Science 12246, 185-193. Cham: Springer. doi: https://doi.org/10.1007/978-3-030-54956-5_14. https://arxiv.org/abs/2006.02770.
- Zielinski, Andrea. 2018. "Text Mining." SS 2018: 2 SWS.