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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

Projects

Current Projects

 Selected closed projects

  • IRM II: Value-Added Services for Information Retrieval II (IRM II)
  • Missy: Service center for microdata

Publications

  • Backes, Tobias. 2018 (Forthcoming). "Keep it Simple: Effective Unsupervised Author Disambiguation with Relative Frequencies." In Proceedings of the 16th ACM/IEEE Joint Conference on Digital Libraries (JCDL'18).
  • Zielinski, Andrea, and Peter Mutschke. 2018. "Towards a Gold Standard Corpus for Variable Detection and Linking in Social Science Publications." In Proceedings of LREC 2018
  • Zielinski, Andrea, and Peter Mutschke. 2017. "Mining Social Science Publications for Survey Variables." In Proceedings of the Second Workshop on Natural Language Processing and Computational Social Science, Vancouver, Canada, August 3, 2017, edited by Dirk Hovy, Svitlana Volkova, and David Bamman, 47–52. Association for Computational Linguistics. aclweb.org/anthology/W17-29. aclweb.org/anthology/W17-29.
  • Interlinking Large-scale Library Data with Authority Records
    Bensmann, Felix, Benjamin Zapilko and Philipp Mayr
  • Hienert, Daniel, and Peter Mutschke. 2016. "A Usefulness-based Approach for Measuring the Local and Global Effect of IIR Services." InCHIIR '16 Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval , 153-162. New York: ACM.http://dx.doi.org/10.1145/2854946.2854962.
  • Mutschke, Peter, and Philipp Mayr. 2015. "Science Models for Search: A Study on Combining Scholarly Information Retrieval and Scientometrics." Scientometrics 102 (3): 2323–2345. doi: http://dx.doi.org/10.1007/s11192-014-1485-2.
  • Hienert, Daniel, Wilko van Hoek, Alina Weber, and Dagmar Kern. 2015. "WHOSE – A Tool for Whole-Session Analysis in IIR." InAdvances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29 - April 2, 2015. Proceedings, Lecture Notes in Computer Science 9022, 172-183. http://arxiv.org/abs/1504.06961.
  • Kern, Dagmar, and Brigitte Mathiak. 2015. "Are there any Differences in Data Set Retrieval compared to well-known Literature Retrieval?." In Research and Advanced Technology for Digital Libraries : 19th International Conference on Theory and Practice of Digital Libraries, TPDL 2015, Poznań, Poland, September 14-18, 2015, Proceedings, Lecture Notes in Computer Science 9316, 197-208.
  • Dulisch, Nadine, Andreas Oskar Kempf, and Philipp Schaer. 2015. "Query Expansion for Survey Question Retrieval in the Social Sciences." In Research and Advanced Technology for Digital Libraries : 19th International Conference on Theory and Practice of Digital Libraries, TPDL 2015, Poznań, Poland, September 14-18, 2015.
  • Zapilko, Benjamin, Johann Schaible, Timo Wandhöfer, and Peter Mutschke. 2015. "Applying linked data technologies in the social sciences." Künstliche Intelligenz : KI online first 1-4. doi: http://dx.doi.org/10.1007/s13218-015-0416-6. http://link.springer.com/article/10.1007/s13218-015-0416-6?wt_mc=internal.event.1.SEM.ArticleAuthorOnlineFirst.
  • Zapilko, Benjamin, and Brigitte Mathiak. 2014. "Object property matching utilizing the overlap between imported ontologies." In The Semantic Web: Trends and Challenges ; 11th International Conference, ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014 ; Proceedings, edited by Valentina Presutti, Claudia d'Amato, and Fabien Gandon, Lecture Notes in Computer Science ; vol. 8465, 737-751. Cham: Springer. http://2014.eswc-conferences.org/sites/default/files/papers/paper_65.pdf.
  • Zapilko, Benjamin, Johann Schaible, Philipp Mayr, and Brigitte Mathiak. 2013. "TheSoz: a SKOS representation of the thesaurus for the social sciences." Semantic Web: interoperabilty, usability, applicability Volume 4, Number 3 257-263. doi: dx.doi.org/10.3233/SW-2012-0081. www.semantic-web-journal.net/content/thesoz-skos-representation-thesaurus-social-sciences.
  • Lüke, Thomas, Philipp Schaer, and Philipp Mayr. 2012. "Improving retrieval results with discipline-specific query expansion." In Theory and practice of digital libraries : second international conference ; proceedings ; TPDL 2012, Paphos, Cyprus, September 23 - 27, 2012, edited by Panayiotis Zaphiris, Georg Buchanan, Edie Rasmussen, and Fernando Loizides, Lecture notes in computer science 7489, 408-413. Berlin: Springer.
  • Mutschke, Peter, Philipp Mayr, Philipp Schaer, and York Sure-Vetter. 2011. "Science models as value-added services for scholarly information systems." Scientometrics 89 (1) 349-364. doi: http://dx.doi.org/10.1007/s11192-011-0430-x.