Extending Term Suggestion with Author Names

  • Philipp Schaer
  • Philipp Mayr
  • Thomas Lüke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7489)


Term suggestion or recommendation modules can help users to formulate their queries by mapping their personal vocabularies onto the specialized vocabulary of a digital library. While we examined actual user queries of the social sciences digital library Sowiport we could see that nearly one third of the users were explicitly looking for author names rather than terms. Common term recommenders neglect this fact. By picking up the idea of polyrepresentation we could show that in a standardized IR evaluation setting we can significantly increase the retrieval performances by adding topical-related author names to the query. This positive effect only appears when the query is additionally expanded with thesaurus terms. By just adding the author names to a query we often observe a query drift which results in worse results.


Term Suggestion Query Suggestion Evaluation Digital Libraries Query Expansion Polyrepresentation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Blair, D.C.: Information retrieval and the philosophy of language. Annual Review of Information Science and Technology 37, 3–50 (2003)CrossRefGoogle Scholar
  2. 2.
    Petras, V.: Translating Dialects in Search: Mapping between Specialized Languages of Discourse and Documentary Languages (2006),
  3. 3.
    Geyer-Schulz, A., Neumann, A., Thede, A.: Others Also Use: A Robust Recommender System for Scientific Libraries. In: Koch, T., Sølvberg, I.T. (eds.) ECDL 2003. LNCS, vol. 2769, pp. 113–125. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  4. 4.
    Nascimento, C., Laender, A.H.F., da Silva, A.S., Gonçalves, M.A.: A source independent framework for research paper recommendation. In: Proceedings of the 11th Annual International ACM/IEEE Joint Conference on Digital Libraries, pp. 297–306. ACM, New York (2011)Google Scholar
  5. 5.
    Hienert, D., Schaer, P., Schaible, J., Mayr, P.: A Novel Combined Term Suggestion Service for Domain-Specific Digital Libraries. In: Gradmann, S., Borri, F., Meghini, C., Schuldt, H. (eds.) TPDL 2011. LNCS, vol. 6966, pp. 192–203. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  6. 6.
    Gollapalli, S.D., Mitra, P., Giles, C.L.: Ranking authors in digital libraries. In: Proceedings of the 11th Annual International ACM/IEEE Joint Conference on Digital Libraries, pp. 251–254. ACM, New York (2011)Google Scholar
  7. 7.
    Heck, T., Hanraths, O., Stock, W.G.: Expert recommendation for knowledge management in academia. Proceedings of the American Society for Information Science and Technology 48, 1–4 (2011)CrossRefGoogle Scholar
  8. 8.
    Mutschke, P., Mayr, P., Schaer, P., Sure, Y.: Science models as value-added services for scholarly information systems. Scientometrics 89, 349–364 (2011)CrossRefGoogle Scholar
  9. 9.
    Ingwersen, P., Järvelin, K.: The turn: Integration of information seeking and retrieval in context. Springer, Dordrecht (2005)zbMATHGoogle Scholar
  10. 10.
    Skov, M., Larsen, B., Ingwersen, P.: Inter and intra-document contexts applied in polyrepresentation for best match IR. Information Processing & Management 44, 1673–1683 (2008)CrossRefGoogle Scholar
  11. 11.
    Larsen, B.: Practical Implications of Handling Multiple Contexts in the Principle of Polyrepresentation. In: Crestani, F., Ruthven, I. (eds.) CoLIS 2005. LNCS, vol. 3507, pp. 20–31. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Philipp Schaer
    • 1
  • Philipp Mayr
    • 1
  • Thomas Lüke
    • 1
  1. 1.GESIS – Leibniz Institute for the Social SciencesCologneGermany

Personalised recommendations