Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Series
نویسندگان
چکیده
Knowing how to construct text-based Search Queries (SQs) for use in Engines (SEs) such as Google or Wikipedia has become a fundamental skill. Though much data are available through SEs, most structured datasets live outside their scope. Visualization tools aid this limitation, but no come close the sheer amount of information general-purpose SEs. To fill gap, paper presents Q4EDA, novel framework that converts users’ visual selection queries executed on top time series representations, providing valid and stable SQs be used SEs suggestions related information. The usefulness Q4EDA is presented validated by users an application linking Gapminder’s line-chart replica with SE populated documents, showing supports enhances exploratory analysis United Nations world indicators. Despite some limitations, unique its proposal represents real advance towards solutions querying textual based user interactions representations.
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ژورنال
عنوان ژورنال: Information
سال: 2022
ISSN: ['2078-2489']
DOI: https://doi.org/10.3390/info13080368