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Interactive Labelled Object Treemap: Visualization Tool for Multiple Hierarchies

  • Conference paper
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Evolution in Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1176))

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Abstract

Visualizing multiple hierarchies is necessary for a variety of applications., i.e. for a given set of objects, to identify object types as well as the relationship between different objects (whether objects are related to one other or not). As the simplest solution, two separate tree diagrams (object tree and taxonomy tree) can be used to display object connections and object types. We have designed an interactive visualization technique that effectively conveys both the necessary information using a single representation. ‘Labeled Object treemap’ is a very well-studied technique for visualizing multiple hierarchies in which objects are connected if and only if their corresponding set labels are disjoint and object types can be identified easily by the background structure, treemap. In this paper, we have designed an interactive version of this technique. In our interactive solution, for the given set of object types, the user can provide any size of input tree in the given textbox. A unique set label is generated for each node, and nodes are distributed and displayed (as small red circles) according to their object types in the rectangle areas of the treemap. Four checkboxes are provided to offer various features. These features are discussed in detail in the paper. Our proposed interactive visualization technique has all the good features of the existing ‘labelled object ‘Treemap’ technique including single representation, high compactness, cluster identification, etc., and solves the issues of edge crossings and continuity.

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Correspondence to Mahipal Jadeja .

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Jadeja, M., Kanakia, H., Muthu, R. (2021). Interactive Labelled Object Treemap: Visualization Tool for Multiple Hierarchies. In: Bhateja, V., Peng, SL., Satapathy, S.C., Zhang, YD. (eds) Evolution in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1176. Springer, Singapore. https://doi.org/10.1007/978-981-15-5788-0_48

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