Toward the operationalization of visual metaphor

Hiniker, Alexis; Hong, Sung‐Soo; Kim, Yea-Seul; Chen, Nan-Chen; West, Jevin D.; Aragon, C.

doi:10.1002/asi.23857

Cited by 7 publications

(3 citation statements)

References 35 publications

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“…Chau [18] also used flowers to represent search results from the web. Hiniker [19] applied visual metaphors for clustering and viewing citations of literature from a large database. Keith [20] used visual metaphors to develop narrative maps for visualizing online narratives.…”

Section: Review Of Related Workmentioning

confidence: 99%

Text2Simulate: A Scientific Knowledge Visualization Technique for Generating Visual Simulations from Textual Knowledge

Ige¹,

Oladejo²

2023

IJACSA

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Recent research has developed knowledge visualization techniques for generating interactive visualizations from textual knowledge. However, when applied, these techniques do not generate precise semantic visual representations, which is imperative for domains that require an accurate visual representation of spatial attributes and relationships between objects of discourse in explicit knowledge. Therefore, this work presents a Text-to-Simulation Knowledge Visualization (TSKV) technique for generating visual simulations from domain knowledge by developing a rule-based classifier to improve natural language processing, and a Spatial Ordering (SO) algorithm to solve the identified challenge. A system architecture was developed to structurally model the components of the TSKV technique and implemented using a Knowledge Visualization application called 'Text2Simulate'. A quantitative evaluation of the application was carried out to test for accuracy using modified existing information visualization evaluation criteria. Object Inclusion (OI), Object-Attribute Visibility (OAV), Relative Positioning (RP), and Exact Visual Representation (EVR) criteria were modified to include Object's Motion (OM) metric for quantitative evaluation of generated visual simulations. Evaluation for accuracy on generated simulation results were 90.1, 84.0, 90.1, 90.0, and 96.0% for OI, OAV, OM, RP, and EVR criteria respectively. User evaluation was conducted to measure system effectiveness and user satisfaction which showed that all the participants were satisfied well above average. These generated results showed an improved semantic quality of visualized knowledge due to the improved classification of spatial attributes and relationships from textual knowledge. This technique could be adopted during the development of electronic learning applications for improved understanding and desirable actions.

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Section: Review Of Related Workmentioning

confidence: 99%

Text2Simulate: A Scientific Knowledge Visualization Technique for Generating Visual Simulations from Textual Knowledge

Ige¹,

Oladejo²

2023

IJACSA

View full text Add to dashboard Cite

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“…Boyle and Gray [50] used 3D structures to visualize database query results, using attributes such as size and position to convey information. More immersive and advanced usages of metaphors include colored virtual reality tunnels for program analysis and comprehension of concurrent programs [51], [52], or interactive map-like interfaces to visualize academic research fields and their similarity to each other [53].…”

Section: A Using Visualization Metaphorsmentioning

confidence: 99%

Memory Cities: Visualizing Heap Memory Evolution Using the Software City Metaphor

Weninger

Makor

Mössenböck

2020

2020 Working Conference on Software Visualization (VISSOFT)

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Tool support is essential to help developers in understanding the memory behavior of complex software systems. Anomalies such as memory leaks can dramatically impact application performance and can even lead to crashes. Unfortunately, most memory analysis tools lack advanced visualizations (especially of the memory evolution over time) that could facilitate developers in analyzing suspicious memory behavior.In this paper, we present Memory Cities, a technique to visualize an application's heap memory evolution over time using the software city metaphor. While this metaphor is typically used to visualize static artifacts of a software system such as class hierarchies, we use it to visualize the dynamic memory behavior of an application. In our approach, heap objects can be grouped by multiple properties such as their types or their allocation sites. The resulting object groups are visualized as buildings arranged in districts, where the size of a building corresponds to the number of heap objects or bytes it represents. Continuously updating the city over time creates the immersive feeling of an evolving city. This can be used to detect and analyze memory leaks, i.e., to search for suspicious growth behavior. Memory cities further utilize various visual attributes to ease this task. For example, they highlight strongly growing buildings using color, while making less suspicious buildings semi-transparent.We implemented memory cities as a standalone application developed in Unity, with a JSON-based interface to ensure easy data import from external tools. We show how memory cites can use data provided by AntTracks, a trace-based memory monitoring tool, and present case studies on different applications to demonstrate the tool's applicability and feasibility.

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“…Recently, Information graphics and the field of information visualization apply a variety of metaphorical devices to make large size, complex, abstract, or otherwise difficult-to-comprehend information understandable in graphical terms [36,37].…”

Section: Constellation Visualizationmentioning

confidence: 99%

An Improved Study of Multilevel Semantic Network Visualization for Analyzing Sentiment Word of Movie Review Data

Han

Mun

et al. 2019

Applied Sciences

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This paper suggests a method for refining a massive amount of collective intelligence data and visualizing it with a multilevel sentiment network in order to understand the relevant information in an intuitive and semantic way. This semantic interpretation method minimizes network learning in the system as a fixed network topology only exists as a guideline to help users understand. Furthermore, it does not need to discover every single node to understand the characteristics of each clustering within the network. After extracting and analyzing the sentiment words from the movie review data, we designed a movie network based on the similarities between the words. The network formed in this way will appear as a multilevel sentiment network visualization after the following three steps: (1) design a heatmap visualization to effectively discover the main emotions on each movie review; (2) create a two-dimensional multidimensional scaling (MDS) map of semantic word data to facilitate semantic understanding of network and then fix the movie network topology on the map; (3) create an asterism graphic with emotions to allow users to easily interpret node groups with similar sentiment words. The research also presents a virtual scenario about how our network visualization can be used as a movie recommendation system. We next evaluated our progress to determine whether it would improve user cognition for multilevel analysis experience compared to the existing network system. Results showed that our method provided improved user experience in terms of cognition. Thus, it is appropriate as an alternative method for semantic understanding.

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Toward the operationalization of visual metaphor

Cited by 7 publications

References 35 publications

Text2Simulate: A Scientific Knowledge Visualization Technique for Generating Visual Simulations from Textual Knowledge

Text2Simulate: A Scientific Knowledge Visualization Technique for Generating Visual Simulations from Textual Knowledge

Memory Cities: Visualizing Heap Memory Evolution Using the Software City Metaphor

An Improved Study of Multilevel Semantic Network Visualization for Analyzing Sentiment Word of Movie Review Data

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