Using adaptive interfaces to improve mobile map-based visualisation

Tonder, Bradley van; Wesson, Janet

doi:10.1145/1456659.1456689

Cited by 9 publications

(6 citation statements)

References 8 publications

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“…The largest group of paper in this category respond indirectly to user interactions [14,27,37,42,44,72]. For example, this category includes systems that update recommended content in response to user actions such as a change to visualization settings, selecting or inspecting visualized objects, or moving and resizing items.…”

Section: Stabilitymentioning

confidence: 99%

“…Recommendations that suggest content that is of a smaller size fit within the finer granularity category. A total of 11 papers [3,4,15,38,42,45,52,58,65,72,77] were identified as fitting into the finer granularity category. As one example, Silva et al [65], describe an approach which builds a hierarchical view of a large data set, and then provides users with recommendations for specific variables or dimensions that yield deeper, lower-level views of the data which move down the hierarchy.…”

Section: Granularitymentioning

confidence: 99%

See 1 more Smart Citation

A Design Space for Surfacing Content Recommendations in Visual Analytic Platforms

Zhou¹,

Wang²,

Guo³

et al. 2022

Preprint

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Recommendation algorithms have been leveraged in various ways within visualization systems to assist users as they perform of a range of information tasks. One common focus for these techniques has been the recommendation of content, rather than visual form, as a means to assist users in the identification of information that is relevant to their task context. A wide variety of techniques have been proposed to address this general problem, with a range of design choices in how these solutions surface relevant information to users. This paper reviews the state-of-the-art in how visualization systems surface recommended content to users during users' visual analysis; introduces a four-dimensional design space for visual content recommendation based on a characterization of prior work; and discusses key observations regarding common patterns and future research opportunities.

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Section: Stabilitymentioning

confidence: 99%

Section: Granularitymentioning

confidence: 99%

A Design Space for Surfacing Content Recommendations in Visual Analytic Platforms

Zhou¹,

Wang²,

Guo³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The basic building blocks of an adaptive cartographic visualization application are identified as the context dimensions, the objects that can be adapted, and the adaptation methods. This framework Tonder et al [23], propose a model that incorporates an adaptive interface in the design of a map visualization system for mobile devices. This model consists of four main components: A "Data Model" that contains the information being displayed in the system; a "Knowledge Base" that manages and obtains the four different types of context used (namely user profile, user task, time and location); the "User Monitoring and Modeling Component", which is responsible for accepting the user interaction data, and to automatically determine the user's preferences and behavior; and the "Adaptation Engine" that manages the adaptations of the visualization (visual representations, detail and zoom level), information (filtering) and interface (menu options).…”

Section: Adaptive Mobile Visualization Frameworkmentioning

confidence: 99%

Adaptive mobile visualization - the chameleon framework

2015

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The evolution of mobile devices and the development of high speed wireless networks have supported a widespread use of these devices with increasingly more complex applications. This reality has fostered the research in the field of information visualization in mobile devices. However, the limited screen space, resource constraints and interaction restrictions impose difficulties to developers and users of these applications. An approach to address these problems is to adapt the visualization to the user context. However, these proposals are normally designed in an ad-hoc fashion and are difficult to generalize. In addition, existing solutions are focused only in some subset of possible characteristics of the user context or only address a very specific domain and related adaptations. The objective of this paper is to present the design of a framework for adaptive mobile visualization (AMV) applications, denominated Chameleon, and the development and evaluation of prototypes that use this conceptual-based framework.

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“…Bradley van Tonder and Janet Wesson [10], propose a model that incorporates an adaptive interface in the design of a map visualization system for mobile devices. Their model consists of four main components: A "Data Model" that contains the information that is being visualized in the system; a "Knowledge Base" that manages and obtains the four different types of context used (namely user profile, user task, time and location); the "User Monitoring and Modelling Component" that is responsible for accepting the user interaction data to try and automatically determine the user's preferences and behavior; and finally the "Adaptation Engine" that manages the adaptations of the visualization (visual representations, detail level, zoom level), information (filtering) and interface (menu options).…”

Section: Related Workmentioning

confidence: 99%