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dc.contributor.authorMazurek, Michaelen_US
dc.contributor.authorWaldner, Manuelaen_US
dc.contributor.editorJeffrey Heer and Heike Leitte and Timo Ropinskien_US
dc.date.accessioned2018-06-02T18:07:20Z
dc.date.available2018-06-02T18:07:20Z
dc.date.issued2018
dc.identifier.issn1467-8659
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.13403
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13403
dc.description.abstractWhen performing queries in web search engines, users often face difficulties choosing appropriate query terms. Search engines therefore usually suggest a list of expanded versions of the user query to disambiguate it or to resolve potential term mismatches. However, it has been shown that users find it difficult to choose an expanded query from such a list. In this paper, we describe the adoption of set-based text visualization techniques to visualize how query expansions enrich the result space of a given user query and how the result sets relate to each other. Our system uses a linguistic approach to expand queries and topic modeling to extract the most informative terms from the results of these queries. In a user study, we compare a common text list of query expansion suggestions to three set-based text visualization techniques adopted for visualizing expanded query results - namely, Compact Euler Diagrams, Parallel Tag Clouds, and a List View - to resolve ambiguous queries using interactive query expansion. Our results show that text visualization techniques do not increase retrieval efficiency, precision, or recall. Overall, users rate Parallel Tag Clouds visualizing key terms of the expanded query space lowest. Based on the results, we derive recommendations for visualizations of query expansion results, text visualization techniques in general, and discuss alternative use cases of set-based text visualization techniques in the context of web search.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectInformation systems
dc.subjectSearch interfaces
dc.subjectHuman
dc.subjectcentered computing
dc.subjectEmpirical studies in visualization
dc.titleVisualizing Expanded Query Resultsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersComparative and Collaborative
dc.description.volume37
dc.description.number3
dc.identifier.doi10.1111/cgf.13403
dc.identifier.pages87-98


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  • 37-Issue 3
    EuroVis 2018 - Conference Proceedings

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