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On Clustered Graph Layouts Sketched by Users Based on Predefined Clusters

Published: 24 August 2015 Publication History

Abstract

The aesthetics for user-sketched layouts of clustered graphs with known clustering information is analyzed empirically. In our experiments, given the adjacency list of a clustered graph and its predefined clustering information, each participant was asked to manually sketch clustered graphs "nicely" from scratch on a tablet system using a stylus. The main feature of this work different from the previous work is to investigate if the user's complex task of sketching clustered graphs "nicely" can be alleviated by providing the cluster partition information. Results show that most participants can draw graphs with clear presence of bridge edges and clustering cohesiveness.

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  1. On Clustered Graph Layouts Sketched by Users Based on Predefined Clusters

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    cover image ACM Other conferences
    VINCI '15: Proceedings of the 8th International Symposium on Visual Information Communication and Interaction
    August 2015
    185 pages
    ISBN:9781450334822
    DOI:10.1145/2801040
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 24 August 2015

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    Author Tags

    1. Graph drawing aesthetics
    2. cluster graph
    3. user-sketched drawing

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    VINCI '15

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    VINCI '15 Paper Acceptance Rate 12 of 32 submissions, 38%;
    Overall Acceptance Rate 71 of 193 submissions, 37%

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