Skip to main content
SpringerLink
Log in

Interaktives Retrieval und situationsabhängige Vorschläge

  • Schwerpunktbeitrag
  • Published:
Datenbank-Spektrum Aims and scope Submit manuscript

Zusammenfassung

In diesem Artikel wird beschrieben, wie ein adaptives Vorschlagssystem für Suchstrategien Interaktives Retrieval unterstützen kann. Ein Benutzerexperiment mit 24 Teilnehmern zeigte, dass ein solches System Suchenden hilft, erfolgreichere Strategien einzusetzen, als Suchende ohne Unterstützung. Die Ergebnisse lassen eine Korrelation zwischen dem Sucherfolg der Teilnehmer (gemessen an der Zahl relevanter gespeicherter Dokumente) und dem Einsatz von Vorschlägen erkennen. Durch Vorschläge unterstützte Suchende setzten zudem signifikant öfter fortgeschrittene Werkzeuge und Optionen des Suchsystems ein – auch nach Abschaltung der Vorschläge während der letzten Aufgabe des Experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Abb. 1

Notes

  1. Das System wird inzwischen unter dem neuen Namen ezDL weiterentwickelt, http://www.ezdl.de.

  2. Bei der Suchstrategie des Pearlgrowing wird zunächst ein relevantes Dokument identifiziert. Dieses nutzt der Suchende dann, um über Deskriptoren, Klassifikationsbegriffe, Titelterme, Zitationen oder Referenzen weitere relevante Dokumente zu finden. Mit den neuen Dokumenten als Quelle kann die Strategie iterativ fortgesetzt werden.

  3. Gefördert durch das European Union Seventh Framework Programme (FP7/2007-2013), grant agreement 257528 (KHRESMOI), http://khresmoi.eu/.

  4. http://www.hon.ch/pat_de.html.

Literatur

  1. Aula A, Nordhausen K (2006) Modeling successful performance in web searching. J Am Soc Inf Sci Technol 57(12):1678–1693

    Article  Google Scholar 

  2. Awasum M (2008) Vorschläge für Google-Suchen als Firefox-Erweiterung. Bachelorarbeit, Universität Duisburg-Essen

  3. Bates MJ (1979) Information search tactics. J Am Soc Inf Sci 30(4):205–214

    Article  Google Scholar 

  4. Bates MJ (1989) The design of browsing and berrypicking techniques for the online search interface. On-Line Rev. 13(5):407–424

    Google Scholar 

  5. Bates MJ (1990) Where should the person stop and the information search interface start? Inf Process Manag 26(5):575–591

    Article  MathSciNet  Google Scholar 

  6. Belkin NJ, Marchetti P, Cool C (1993) BRAQUE: Design of an interface to support user interaction in information retrieval. Inf Process Manag 29(3):325–344

    Article  Google Scholar 

  7. Belkin NJ, Cool C, Stein A, Thiel U (1995) Cases, scripts, and information-seeking strategies: on the design of interactive information retrieval systems. Expert Syst Appl 9(3):379–395

    Article  Google Scholar 

  8. Bhavnani SK, Drabenstott K, Radev D (2001) Towards a unified framework of IR tasks and strategies. In: Proceedings of the ASIST, S 340–354

    Google Scholar 

  9. Brajnik G, Mizzaro S, Tasso C (1996) Evaluating user interfaces to information retrieval systems: A case study on user support. In: Proceedings of the 19th annual international ACM SIGIR conference on research and development in information retrieval. ACM, New York, S 128–136

    Chapter  Google Scholar 

  10. Brajnik G, Mizzaro S, Tasso C, Venuti F (2002) Strategic help in user interfaces for information retrieval. J Am Soc Inf Sci Technol 53(5):343–358

    Article  Google Scholar 

  11. Carstens C, Rittberger M, Wissel V (2009) How users search in the German education index—tactics and strategies. In: Proceedings of the workshop IR at the LWA, S 2009

    Google Scholar 

  12. Drabenstott KM (2003) Do nondomain experts enlist the strategies of domain experts. J Am Soc Inf Sci Technol 54(9):836–854

    Article  Google Scholar 

  13. Fields B, Keith S, Blandford A (2004) Designing for expert information finding strategies. In: Fincher S, Markopoulos P, Moore D, Ruddle RA (Hrsg) BCS HCI. Springer, Berlin, S 89–102

    Google Scholar 

  14. Fuhr N, Klas CP, Schaefer A, Mutschke P (2002) Daffodil: an integrated desktop for supporting high-level search activities in federated digital libraries. In: Research and advanced technology for digital libraries. 6th European conference, ECDL 2002. Springer, Heidelberg, S 597–612

    Chapter  Google Scholar 

  15. Harter SP (1986) Online information retrieval: concepts, principles, and techniques. Academic Press, San Diego

    Google Scholar 

  16. Harter SP, Peters AR (1985) Heuristics for online information retrieval: a typology and preliminary listing. On-Line Rev. 9(5):407–424

    Google Scholar 

  17. Hsieh-Yee I (1993) Effects of search experience and subject knowledge on online search behavior: measuring the search tactics of novice and experienced searchers. J Am Soc Inf Sci 44(3):161–174

    Article  Google Scholar 

  18. Jansen BJ (2005) Seeking and implementing automated assistance during the search process. Inf Process Manag 41(4):909–928

    Article  Google Scholar 

  19. Jansen BJ, McNeese MD (2005) Evaluating the effectiveness of and patterns of interactions with automated searching assistance: research articles. J Am Soc Inf Sci Technol 56(14):1480–1503

    Article  Google Scholar 

  20. Järvelin K (2009) Explaining user performance in information retrieval: challenges to IR evaluation. In: Azzopardi L, Kazai G, Robertson SE, Rüger SM, Shokouhi M, Song D, Yilmaz E (Hrsg) ICTIR 2009. Lecture notes in computer science, Bd 5766. Springer, Berlin, S 289–296

    Google Scholar 

  21. Keskustalo H, Järvelin K, Pirkola A, Sharma T, Lykke Nielsen M (2009) Test collection-based IR evaluation needs extension toward sessions—a case of extremely short queries. In: AIRS 2009, 5th Asia information retrieval symposium. Lecture notes in computer science, vol 5839. Springer, Berlin, S 63–74

    Google Scholar 

  22. Klas CP, Fuhr N, Schaefer A (2004) Evaluating strategic support for information access in the DAFFODIL system. In: Research and advanced technology for digital libraries. Proceedings of the ECDL. Springer, Heidelberg, S 476–487

    Chapter  Google Scholar 

  23. Kriewel S (2010) Unterstützung beim Finden und Durchführen von Suchstrategien in Digitalen Bibliotheken. PhD thesis, University of Duisburg-Essen

  24. Kriewel S, Fuhr N (2007) Adaptive search suggestions for digital libraries. In: Asian digital libraries: looking back 10 years and forging new frontiers (ICADL 2007), S 220–229

    Chapter  Google Scholar 

  25. Kriewel S, Fuhr N (2010) An evaluation of an adaptive search suggestion system. In: 32nd European conference on information retrieval research (ECIR 2010). Springer, Heidelberg

    Google Scholar 

  26. Kriewel S, Klas CP, Schaefer A, Fuhr N (2004) Daffodil—strategic support for user-oriented access to heterogeneous digital libraries. D-Lib Mag 10(6):2–7

    Google Scholar 

  27. Kuhlthau CC (2003) Seeking meaning: a process approach to library and information services, 2 Aufl. Libraries Unlimited Inc, Westport

    Google Scholar 

  28. Lin SJ, Belkin NJ (2000) Modeling multiple information seeking episodes. In: Proceedings of the 63rd annual meeting of the American society for information science and technology, Bd 37, S 133–147

    Google Scholar 

  29. Marchionini G (1989) Information-seeking strategies of novices using a full-text electronic encyclopedia. J Am Soc Inf Sci 40(1):54–66

    Article  Google Scholar 

  30. Markey K (2007) Twenty-five years of end-user searching. Part 1. Research findings. J Am Soc Inf Sci Technol 58(8):1071–1081

    Article  Google Scholar 

  31. Markey K (2007) Twenty-five years of end-user searching. Part 2. Future research directions. J Am Soc Inf Sci Technol 58(8):1123–1130

    Article  Google Scholar 

  32. Ontañón S, Plaza E (2003) Justification-based multiagent learning. In: Fawcett TNM (Hrsg) The twentieth international conference on machine learning (ICML 2003), Bd ICML, S 576–583, AAAI Press, Menlo Park

    Google Scholar 

  33. Pollock A, Hockley A (1997) What’s wrong with internet searching. D-Lib Mag

  34. Rieh SY, Xie HI (2001) Patterns and sequences of multiple query reformulations in web searching: a preliminary study. In: Proceedings of the 64th annual meeting of the ASIST, Bd 38, S 246–255

    Google Scholar 

  35. Schaefer A, Jordan M, Klas CP, Fuhr N (2005) Active support for query formulation in virtual digital libraries: a case study with DAFFODIL. In: Research and advanced technology for digital libraries, proceedings of the ECDL. Springer, Heidelberg

    Google Scholar 

  36. Wildemuth BM (2004) The effects of domain knowledge on search tactic formulation. J Am Soc Inf Sci Technol 55(3):246–258

    Article  Google Scholar 

  37. Xie HI (2000) Shifts of interactive intentions and information-seeking strategies in interactive information retrieval. J Am Soc Inf Sci 51(9):841–857

    Article  Google Scholar 

  38. Xie I, Cool C (2009) Understanding help seeking within the context of searching digital libraries. J Am Soc Inf Sci Technol 60(3):477–494

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Abteilung für Informatik und Angew. Kognitionswissenschaft, Universität Duisburg-Essen, Duisburg, Deutschland

    Sascha Kriewel

Authors
  1. Sascha Kriewel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sascha Kriewel.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kriewel, S. Interaktives Retrieval und situationsabhängige Vorschläge. Datenbank Spektrum 11, 173–181 (2011). https://doi.org/10.1007/s13222-011-0063-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13222-011-0063-5

Search

Navigation