Visualizing Expanded Query Results

Michael Mazurek, Manuela Waldner
Visualizing Expanded Query Results
Computer Graphics Forum:87-98, June 2018. [paper]

Information

Abstract

When 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.

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teaser: Density-based compact Euler Diagram teaser: Density-based compact Euler Diagram

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BibTeX

@article{mazurek-2018-veq,
  title =      "Visualizing Expanded Query Results",
  author =     "Michael Mazurek and Manuela Waldner",
  year =       "2018",
  abstract =   "When 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.",
  month =      jun,
  journal =    "Computer Graphics Forum",
  pages =      "87--98",
  keywords =   "Information visualization, search interfaces, empirical
               studies in visualization",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/",
}