Fractal approaches for visualizing huge hierarchies

Koike, Hideki; Yoshihara, Hiroki

doi:10.1109/vl.1993.269566

Cited by 53 publications

(38 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More abstract and global-oriented strategies to represent visuo-spatial information seem to be more efficient because they allow the compression, or reduction, of the information required to be kept online (Alvarez, 2011). In computer science, fractal strategies have also been shown to be efficient in the representation of complex hierarchies, precisely by compressing the amount of information (Koike & Yoshihara, 1993). From this discussion sprouts the prediction that recursive modes of representation are more abstract and lead to better compression of information.…”

Section: Hierarchical Processing In the Visual Domainmentioning

confidence: 98%

A novel approach to investigate recursion and iteration in visual hierarchical processing

Martins

Martins²,

Fitch

2015

Behav Res

View full text Add to dashboard Cite

We describe a new method to explore recursive cognition in the visual domain. We define recursion as the ability to represent multiple hierarchical levels using the same rule, entailing the ability to generate new levels beyond those previously encountered. With this definition recursion can be distinguished from general hierarchical embedding. To investigate this recursion/hierarchy distinction in the visual domain, we developed two novel methods: The Visual Recursion Task (VRT), in which an inferred rule is used to represent new hierarchical levels, and the Embedded Iteration Task (EIT), in which additional elements are added to an existing hierarchical level. We found that adult humans can represent recursion in the visuo-spatial domain, and that this ability is distinct from both general intelligence and the ability to represent iterative processes embedded within hierarchical structures. Compared with embedded iteration, visual recursion correlated positively with other recursive planning tasks (Tower of Hanoi), but not with specific visuo-spatial resources (spatial short-term memory and working memory). We conclude that humans are able to use recursive representations to process complex visuo-spatial hierarchies and that our visual recursion task taps into specific cognitive resources. This method opens exciting opportunities to explore the relationship between visual recursion and language.Keywords Recursion . Iteration . Cognition . Vision . Fractals . RepresentationThe capacity to understand and generate complex hierarchies is one of the most fascinating features of human cognition. In many domains, including language, music, problem-solving, action-sequencing, and spatial navigation, humans organize basic elements into higher-order groupings and structures (Badre, 2008;Chomsky, 1957;Hauser, Chomsky, & Fitch, 2002; Nardini, Jones, Bedford, & Braddick, 2008;Unterrainer & Owen, 2006;Wohlschlager, Gattis, & Bekkering, 2003). This ability to encode the relationship between basic elements (words, people, etc.) and the broader structures in which these are embedded (sentences, corporations, etc.), affords flexibility to human behavior. For example, in action sequencing, and unlike pure serial associative behavior, hierarchical representations allow the omission or modification of certain steps, without impairing the overall goal.Here, we define hierarchies as non-cyclical tree-like organizations, where higher levels incorporate multiple lower levels in structural representations (Fitch & Martins, 2014), i.e., in which elements are embedded within other elements. This embedding can refer to the grouping of constituents within a higher order set, such as the grouping of individuals within a family (family = {ind1; ind2; ind3}), or it can refer to the establishment of asymmetrical dominance-subordination relationships between constituents, such as in social hierarchies (ind1 dominant over ind2, ind2 dominant over ind3, etc.).Electronic supplementary material The online version of this article

show abstract

Section: Hierarchical Processing In the Visual Domainmentioning

confidence: 98%

A novel approach to investigate recursion and iteration in visual hierarchical processing

Martins

Martins²,

Fitch

2015

Behav Res

View full text Add to dashboard Cite

show abstract

“…the combination of primitive concepts into new concepts [33], an important feature of human creativity [34]). In this regard, it is important to note that these properties are distinct from cognitive grouping (often taken as a synonym of recursion [11,23,32] (2) Recursion is an efficient method to encode complex hierarchies whether or not they were generated recursively [27,39,42]: if a given observer is able to build a compressed abstract representation of an entire hierarchy, then he can focus his attention on a small subset of constituents without losing track of the contextual ensemble. An eventual orthogonal and simultaneous representation of both the whole (abstract) and the details (perceptual) would constitute an efficient and accurate real-time strategy to parse complex hierarchical information.…”

Section: What Is Recursion Good For?mentioning

confidence: 99%

Distinctive signatures of recursion

Martins

2012

Phil. Trans. R. Soc. B

View full text Add to dashboard Cite

Although recursion has been hypothesized to be a necessary capacity for the evolution of language, the multiplicity of definitions being used has undermined the broader interpretation of empirical results. I propose that only a definition focused on representational abilities allows the prediction of specific behavioural traits that enable us to distinguish recursion from non-recursive iteration and from hierarchical embedding: only subjects able to represent recursion, i.e. to represent different hierarchical dependencies (related by parenthood) with the same set of rules, are able to generalize and produce new levels of embedding beyond those specified a priori (in the algorithm or in the input). The ability to use such representations may be advantageous in several domains: action sequencing, problem-solving, spatial navigation, social navigation and for the emergence of conventionalized communication systems. The ability to represent contiguous hierarchical levels with the same rules may lead subjects to expect unknown levels and constituents to behave similarly, and this prior knowledge may bias learning positively. Finally, a new paradigm to test for recursion is presented. Preliminary results suggest that the ability to represent recursion in the spatial domain recruits both visual and verbal resources. Implications regarding language evolution are discussed.

show abstract

“…Visual representation of these models is not an easy task, as an increase of visual elements is detrimental to the human's cognitive load as well as to the system's response time [KY93]. For instance, most CASE (Computer Aided Software Engineering) tools require arrangements 'by hand' [TH05], which means that a great amount of time is spent dragging elements to form a decipherable diagram.…”

Section: Visual Approachesmentioning

confidence: 99%

“…Scrolling endlessly through a diagram is of no practical use [KY93], so we need mechanisms for encoding visually large models without losing 'the big picture'. Focus-plus-Context [Mun00] views, as well as other techniques that involve self-organizing layouts can be used to keep the context.…”

Section: Keep the Context (Kc)mentioning

confidence: 99%

Evaluating the capabilities of Enterprise Architecture modeling tools for Visual Analysis.

Naranjo¹,

Sánchez²,

Villalobos³

2015

JOT

View full text Add to dashboard Cite

In model analysis activities, it is critical to make early statements and diagnosis from a high level of abstraction. Currently, these tasks are difficult to perform, and they require both the involvement of experts and the elaboration of specialized artifacts. Furthermore, the complexity of the tasks increases as models become bigger and more detailed. In other contexts, it has been noticed that total / holistic / unfiltered visualizations may give insight about the models, providing analysts a starting point for exploration and general pattern discovery.In this paper, we evaluate the support that six different Enterprise Architecture (EA) modeling tools offer to EA analysis activities, and assess the strengths and weaknesses of six visualization frameworks, in order to extend the analysis of enterprise models by Visual Analysis. The evaluation is based on a set of 14 requirements which are either visualization-related or specific to EA analysis, and its results were harvested from a) observed characteristics of the diagrams of these tools, and b) visualizations from an enterprise model, generated with the aforementioned visualization frameworks. These results point to several actionable subjects and research opportunities for the field of EA Modeling and Analysis.

show abstract

Fractal approaches for visualizing huge hierarchies

Cited by 53 publications

References 13 publications

A novel approach to investigate recursion and iteration in visual hierarchical processing

A novel approach to investigate recursion and iteration in visual hierarchical processing

Distinctive signatures of recursion

Evaluating the capabilities of Enterprise Architecture modeling tools for Visual Analysis.

Contact Info

Product

Resources

About