Visualizations in Exploratory Search: A User Study with Stock Market Information
Daniel Hienert, Philipp Mayr

TL;DR
This paper introduces an interactive visualization approach for exploratory search in stock market data, enabling users to access, combine, and explore large information sets efficiently, demonstrated through a user study.
Contribution
It presents a novel visualization-based search model that integrates web information and supports complex exploratory tasks without instructions.
Findings
Users completed complex tasks easily
Participants accessed related information efficiently
Knowledge acquisition was rapid in unfamiliar domains
Abstract
In this paper we present an approach that integrates interactive visualizations in the exploratory search process. In this model visualizations can act as hubs where large amounts of information are made accessible in easy user interfaces. Through interaction techniques this information can be combined with related information on the World Wide Web. We applied the new search concept to the domain of stock market information and conducted a user study. Participants could use this interface without instructions, could complete complex tasks like identifying related information items, link heterogeneous information types and use different interaction techniques to access related information more easily. In this way, users could quickly acquire knowledge in an unfamiliar domain.
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Taxonomy
TopicsData Visualization and Analytics · Semantic Web and Ontologies · Video Analysis and Summarization
