Wie Nutzer mit Suchvorschlägen umgehen: Eine explorative Studie

Bayer, Jacqueline Wie Nutzer mit Suchvorschlägen umgehen: Eine explorative Studie. Young Information Scientist, 2017, vol. 2, pp. 13-24. [Journal article (Paginated)]

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English abstract

How users interact with query suggestions: An explorative study [translated title]. Objective — This paper examines the influence of the query types defined by Broder (2002) on the use of query suggestions during input in web search. Methods — In an explorative user study each of 18 participants resolved 21 search tasks. Their behaviour was protocolled via desktop recording and keylogging. How users interact with query suggestions: An explorative study [translated title]. Results — Query suggestions were adopted in 54 % of all queries. If no suggestion was taken, the user input and query suggestions matched in almost 80 %. Results suggest that a query suggestion is only taken if it completely matches the user’s internal query. Conclusions — Query suggestions work well for navigational queries, but poorly for informational ones. There are mainly four reasons for query suggestion use: Speed (shorten typing process), success (suggested queries produce better results), inspiration and spell checking.

German abstract

Zielsetzung — Dieser Artikel untersucht den Einfluss der von Broder (2002) definierten Suchanfragetypen auf den Umgang mit Suchvorschlägen von Websuchmaschinen während der Eingabe. Forschungsmethoden — In einer explorativen Nutzerstudie bearbeiteten 18 Probanden je 21 Rechercheaufgaben. Ihr Verhalten wurde durch Bildschirmaufzeichnung und Keylogging protokolliert. Ergebnisse — In 54 % der Anfragen wurden Suchvorschläge angenommen. Wenn kein Suchvorschlag angenommen wurde, stimmte die Eingabe des Nutzers in fast 80 % der Fälle mit einem der Suchvorschläge überein. Die Ergebnisse deuten darauf hin, dass ein Suchvorschlag erst angenommen wird, wenn die gewünschte Suchanfrage komplett darin abgebildet wird. Schlussfolgerungen — Suchvorschläge unterstützen zielsicher navigationsorientierte Anfragen, informationsorientierte jedoch nur unzureichend. Im Wesentlichen werden sie aus vier Gründen genutzt: Schnelligkeit (Tippvorgang abkürzen), Erfolg (vorgeschlagene Anfrage erzeugt bessere Ergebnisse), Inspiration und Rechtschreibkontrolle.

Item type: Journal article (Paginated)
Keywords: query suggestions, web search, Google, user study, user behaviour, search engines, query type, Suchvorschläge, Websuche, Google, Nutzerstudie, Nutzerverhalten, Suchmaschinen, Suchanfragetyp
Subjects: C. Users, literacy and reading. > CB. User studies.
H. Information sources, supports, channels. > HQ. Web pages.
L. Information technology and library technology > LS. Search engines.
Depositing user: Otto Oberhauser
Date deposited: 02 Aug 2017 12:27
Last modified: 02 Aug 2017 12:27
URI: http://hdl.handle.net/10760/31363

References

Belkin, N. J.; Cool, C.; Head, J. u. a. (2000). Relevance feedback versus local context analysis as term suggestion devices: Rutgers’ trec-8 interactive track experience. In: Proceedings of the eighth text retrieval conference (trec 8). Hrsg. von Voorhees, E. M.; Harman, D. K. Washington, DC, S. 565–576.

Belkin, N. J.; Cool, C.; Kelly, D. u. a. (2001). Iterative exploration, design and evaluation of support for query reformulation in interactive information retrieval. In: Information Processing & Management 37(3), S. 403–434. doi: 10.1016/s0306-4573(00)00055-8.

Berget, G.; Sandnes, F. E. (2015). Do autocomplete functions reduce the impact of dyslexia on information-searching behavior? the case of google. In: Journal of the Association for Information Science and Technology 67(10), S. 2320–2328. doi: 10.1002/asi.23572.

Boldi, P.; Bonchi, F.; Castillo, C. u. a. (2009). Query suggestions using query-flow graphs. In: Proceedings of the 2009 workshop on web search click data - WSCD ’09. Hrsg. von Craswell, N.; Jones, R.; Dupret, G.; Viegas, E. Association for Computing Machinery (ACM), S. 56–63. doi: 10.1145/1507509.1507518.

Broder, A. (2002). A taxonomy of web search. In: ACM SIGIR Forum 36(2), S. 3–10. doi: 10.1145/792550.792552.

Efthimiadis, E. N. (2000). Interactive query expansion: a user-based evaluation in a relevance feedback environment. In: Journal of the American Society for Information Science 51(11), S. 989–1003.

Huang, C.-K.; Chien, L.-F.; Oyang, Y.-J. (2003). Relevant term suggestion in interactive web search based on contextual information in query session logs. In: Journal of the American Society for Information Science and Technology 54(7), S. 638–649. doi: 10.1002/asi.10256.

Kelly, D.; Cushing, A.; Dostert, M. u. a. (2010). Effects of popularity and quality on the usage of query suggestions during information search. In: Proceedings of the 28th international conference on human factors in computing systems - CHI ’10. Association for Computing Machinery (ACM), S. 45–54. doi: 10.1145/1753326.1753334.

Kelly, D.; Dollu, V. D.; Fu, X. (2005). The loquacious user: a document-independent source of terms for query expansion. In: Proceedings of the 28th annual international ACM SIGIR conference on research and development in information retrieval - SIGIR ’05. Association for Computing Machinery (ACM), S. 457–464. doi: 10.1145/1076034.1076112.

Kelly, D.; Gyllstrom, K.; Bailey, E. W. (2009). A comparison of query and term suggestion features for interactive searching. In: Proceedings of the 32nd international ACM SIGIR conference on research and development in information retrieval - SIGIR ’09. Association for Computing Machinery (ACM), S. 371–378. doi: 10.1145/1571941.1572006.

Lewandowski, D.; Quirmbach, S. (2013). Suchvorschläge während der Eingabe. In: Handbuch Internet-Suchmaschinen. Bd. 3: Suchmaschinen zwischen Technik und Gesellschaft. Hrsg. von Lewandowski, D. Berlin: AKA Verlag, S. 273–298.

Mei, Q.; Zhou, D.; Church, K. (2008). Query suggestion using hitting time. In: Proceeding of the 17th ACM conference on information and knowledge mining - CIKM ’08. Association for Computing Machinery (ACM), S. 469–478. doi: 10.1145/1458082.1458145.

Niu, X.; Kelly, D. (2014). The use of query suggestions during information search. In: Information Processing & Management 50(1), S. 218–234. doi: 10.1016/j.ipm.2013.09.002.

Shiri, A.; Revie, C. (2006). Query expansion behavior within a thesaurus-enhanced search environment: A user-centered evaluation. In: Journal of the American Society for Information Science and Technology 57(4), S. 462–478. doi: 10.1002/asi.20319.

Sihvonen, A.; Vakkari, P. (2004). Subject knowledge improves interactive query expansion assisted by a thesaurus. In: Journal of Documentation 60(6), S. 673–690. doi: 10.1108/00220410410568151.

Tang, M.-C.; Wu, W.-C.; Hung, B.-W. (2009). Evaluating a metadata-based term suggestion interface for PubMed with real users with real requests. In: Proceedings of the American Society for Information Science and Technology 46(1), S. 1–18. doi: 10.1002/meet.2009.1450460238.

Vakkari, P. (2002). Subject knowledge, source of terms, and term selection in query expansion: An analytical study. In: European conference on information retrieval. Berlin u. a.: Springer, S. 110–123.

Ward, D.; Hahn, J.; Feist, K. (2012). Autocomplete as a research tool: a study on providing search suggestions. In: Information Technology and Libraries 31(4), S. 6.

White, R. W.; Marchionini, G. (2007). Examining the effectiveness of real-time query expansion. In: Information Processing & Management 43(3), S. 685–704. doi: 10.1016/j.ipm.2006.06.005.


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