Information
- Publication Type: Journal Paper with Conference Talk
- Workgroup(s)/Project(s):
- Date: June 2018
- Journal: Computer Graphics Forum
- Location: Brno, Czech Republic
- Lecturer: Michael Mazurek
- Event: EG / VGTC Conference on Visualization (EuroVis)
- Call for Papers: Call for Paper
- Conference date: 4. June 2018 – 8. June 2018
- Pages: 87 – 98
- Keywords: Information visualization, search interfaces, empirical studies in visualization
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.Additional Files and Images
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No further information available.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/",
}