SeMap: A Concept for the Visualization of Semantics as Maps

Nazemi, Kawa; Breyer, Matthias; Hornung, Christoph

doi:10.1007/978-3-642-02713-0_9

Cited by 18 publications

(13 citation statements)

References 7 publications

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“…Additionally, the result of the question "Would you use the system in the future for similar searching tasks?" confirms the assumption that users prefer the visualization to the list presentation (list: M = 3.14; SD = 0.87; visualization: M = 4.25; SD = 0.77) 8 .…”

Section: Resultssupporting

confidence: 70%

Semantics Visualization for Fostering Search Result Comprehension

Stab

Nazemi

Breyer

et al. 2012

Lecture Notes in Computer Science

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Abstract. Current search engines present search results in an ordered list even if semantic technologies are used for analyzing user queries and the document contents. The semantic information that is used during the search result generation mostly remains hidden from the user although it significantly supports users in understanding why search results are considered as relevant for their individual query. The approach presented in this paper utilizes visualization techniques for offering visual feedback about the reasons the results were retrieved. It represents the semantic neighborhood of search results, the relations between results and query terms as well as the relevance of search results and the semantic interpretation of query terms for fostering search result comprehension. It also provides visual feedback for query enhancement. Therefore, not only the search results are visualized but also further information that occurs during the search processing is used to improve the visual presentation and to offer more transparency in search result generation. The results of an evaluation in a real application scenario show that the presented approach considerably supports users in assessment and decision-making tasks and alleviates information seeking in digital semantic knowledge bases.

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Section: Resultssupporting

confidence: 70%

Semantics Visualization for Fostering Search Result Comprehension

Stab

Nazemi

Breyer

et al. 2012

Lecture Notes in Computer Science

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“…if the user is interested in the city, she would choose the category of cities or locations (depending on the schema). But another main aspect is that the user gets the categories of all instances of her search in a single and comprehensible graphical view [NBH09] that enables a comprehension of the entire searched term and leads to a learning effect [NBS * 10].…”

Section: Inclusion Of Semantics By Iterative Queryingmentioning

confidence: 99%

“…It has more the character of gathering domain knowledge on an abstract level rather than navigating through the hierarchy to the concept or instance of interest. To provide a real hierarchical view on data and enable the navigation through the sub-concept hierarchy, we developed the SeMap visual layout [NBH09].…”

Section: Hierarchical Visual Layoutsmentioning

confidence: 99%

“…SeMap combines two different visual layouts to provide on the one a more goal-directed navigation through the conceptual hierarchies and on the other hand an overview on the contextual hierarchical path that leads to comprehend the knowledge path [NBH09]. Therefore, we used Shneiderman's Treemap [Shn92,SP09] and Treeview that leads to navigate through certain levels of hierarchies.…”

Section: Hierarchical Visual Layoutsmentioning

confidence: 99%

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Adaptive Semantics Visualization

Nazemi¹

2016

Studies in Computational Intelligence

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Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users' behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field. VII VIIIFinally, I thank my loved ones -my wife Mariam, my son Kian, my brothers and parents for their unlimited support, love, and patience.

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“…Multiscale graph visualization allows interactive representations of hierarchical information [13] and provides scalable visualization with abstraction of detail and clutter at different scales [14]. Semantic maps introduce a new visualization technique based on semantically annotated data and the implicit impartation of knowledge [15].…”

Section: Introductionmentioning

confidence: 99%

Hyperbolic Wheel: A Novel Hyperbolic Space Graph Viewer for Hierarchical Information Content

Lam

Dinov²

2012

ISRN Computer Graphics

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Tree and graph structures have been widely used to present hierarchical and linked data. Hyperbolic trees are special types of graphs composed of nodes (points or vertices) and edges (connecting lines), which are visualized on a non-Euclidean space. In traditional Euclidean space graph visualization, distances between nodes are measured by straight lines. Displays of large graphs in Euclidean spaces may not utilize efficiently the available space and may impose limitations on the number of graph nodes. The special hyperbolic space rendering of tree-graphs enables adaptive and efficient use of the available space and facilitates the display of large hierarchical structures. In this paper we report on a newly developed advanced hyperbolic graph viewer, Hyperbolic Wheel, which enables the navigation, traversal, discovery and interactive manipulation of information stored in large hierarchical structures. Examples of such structures include personnel records, disc directory structures, ontological constructs, web-pages and other nested partitions. The Hyperbolic Wheel framework provides an intuitive and dynamic graphical interface to explore and retrieve information about individual nodes (data objects) and their relationships (data associations). The Hyperbolic Wheel is freely available online for educational and research purposes.

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SeMap: A Concept for the Visualization of Semantics as Maps

Cited by 18 publications

References 7 publications

Semantics Visualization for Fostering Search Result Comprehension

Semantics Visualization for Fostering Search Result Comprehension

Adaptive Semantics Visualization

Hyperbolic Wheel: A Novel Hyperbolic Space Graph Viewer for Hierarchical Information Content

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