2020
DOI: 10.1111/cgf.13995
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GTMapLens: Interactive Lens for Geo‐Text Data Browsing on Map

Abstract: Data containing geospatial semantics, such as geotagged tweets, travel blogs, and crime reports, associates natural language texts with geographical locations. This paper presents a lens‐based visual interaction technique, GTMapLens, to flexibly browse the geo‐text data on a map. It allows users to perform dynamic focus+context exploration by using movable lenses to browse geographical regions, find locations of interest, and perform comparative and drill‐down studies. Geo‐text data is visualized in a way that… Show more

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Cited by 7 publications
(6 citation statements)
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“…We introduce the Front-end Visualization of ClinicLens, which enables iterative closed-loop explorations of clinic testing capacity across multiple collaborative visual views. The in-process visual exploration is followed by requirements and started from inspiration by the visual metaphor "Lens on Map [15]", concurrently implementing other views and interactions that dynamically bridge the connection to the Back-end Engine.…”
Section: Front-end Visualizationmentioning
confidence: 99%
“…We introduce the Front-end Visualization of ClinicLens, which enables iterative closed-loop explorations of clinic testing capacity across multiple collaborative visual views. The in-process visual exploration is followed by requirements and started from inspiration by the visual metaphor "Lens on Map [15]", concurrently implementing other views and interactions that dynamically bridge the connection to the Back-end Engine.…”
Section: Front-end Visualizationmentioning
confidence: 99%
“…Meanwhile, papers that deal with simpler embedding techniques, seem to prioritize building an intuitive and effective visual interface with overlay for users to explore. In the paper GTMapLens [MZAD * 20], Ma et al propose a lens‐based visual interaction technique that provides word recommendations to users. When a user explores a geographical region and inputs a keyword of interest, the content of the lens will automatically trace and highlight closely related words.…”
Section: Categorization Of Va + Embedding Approachesmentioning
confidence: 99%
“…However, the challenges of analyzing urban data are highly dependent on specific techniques, since data may come from multiple sources, such as maps, traffic flows, human movement trajectories, loop sensors, acoustic sensors, social applications, etc. Although the generalized workflow may consist of data retrieval, parsing, analysis, evaluation, and visualization [Hu18, MZAD * 20], the specifics are highly dependent on the desired use case and context of research questions. For example, the design considerations for a real‐time monitoring system would be different from an offline analysis tool.…”
Section: Categorization Of Va + Embedding Approachesmentioning
confidence: 99%
“…Geo‐text analysis and visualization is a developing area of research that, when done effectively, may overcome some challenges associated with communicating neighborhood change that use complex algorithms such as the SOM, discussed in the previous section. Solutions for linking natural language processing with geographical visualization are an active area of research that neighborhood dynamics research would benefit from engaging with (Hu, 2018; Ma et al., 2020; Martin & Schuurman, 2017).…”
Section: Looking Forward: Understanding Changes In Near Real Time And...mentioning
confidence: 99%