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DOI: 10.3724/SP.J.2096-5796.21.00040

A balanced-partitioning treemapping method for digital hierarchical dataset


The problem of visualizing a hierarchical dataset is an important and useful  technical in many real happened situations. Folder system, stock market, and other hierarchical related  dataset can use this technical for better understanding the structure, dynamic variation of the dataset. Traditional space-filling(square) based methods have advantages of compact space usage, node size  showing compared to diagram based methods. While space-filling based methods have two main  research directions—static and dynamic performance. We present a treemapping method based on  balanced partitioning that enables in one variant very good aspect ratios, in another good temporal  coherence for dynamic data and in the third a good compromise between these two aspects. To layout  a treemap, we divide all children of a node into two groups. These groups are further divided until we  reach groups of single elements. Then these groups are combined to form the rectangle representing  the parent node. This process is performed for each layer of a given hierarchical dataset. In one variant  of our partitioning we sort child elements first and built two as equal as possible sized groups from big  and small elements(size-balanced partition), which achieves good aspect ratios for the rectangles, but  less good temporal coherence(dynamic). The second variant takes the sequence of children and creates  the as equal as possible groups with-out sorting(sequence-based, good compromise between aspect  ratio and temporal coherency). The third variant splits the children sets always into two groups of  equal cardinality regardless of their size(number-balanced, worse aspect ratios but good temporal  coherence). We evaluate aspect ratios and dynamic stability of our methods and propose a new metric  that measures the visual difference between rectangles during their movement for representing  temporally changing inputs. We demonstrate that our treemapping via balanced partitioning out  performs state-of-the-art methods for a number of real-world datasets.

Cite this article

Cong FENG, Minglun GONG, Oliver DEUSSEN. A balanced-partitioning treemapping method for digital hierarchical dataset. Virtual Reality & Intelligent Hardware DOI:10.3724/SP.J.2096-5796.21.00040