### Abstract

Parallel coordinates are an established technique to visualize high-dimensional data, in particular for data mining purposes. A major challenge is the ordering of axes, as any axis can have at most two neighbors when placed in parallel on a 2D plane. By extending this concept to a 3D visualization space we can place several axes next to each other. However, finding a good arrangement often does not necessarily become easier, as still not all axes can be arranged pairwise adjacently to each other. Here, we provide a tool to explore complex data sets using 3D-parallel-coordinate-trees, along with a number of approaches to arrange the axes.

Original language | English |
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Title of host publication | Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data |

Publisher | Association for Computing Machinery |

Publication date | 29. Jul 2013 |

Pages | 1009-1012 |

ISBN (Print) | 978-1-4503-2037-5 |

DOIs | |

Publication status | Published - 29. Jul 2013 |

Externally published | Yes |

Event | 2013 ACM SIGMOD Conference on Management of Data - New York, United States Duration: 22. Jun 2013 → 27. Jun 2013 |

### Conference

Conference | 2013 ACM SIGMOD Conference on Management of Data |
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Country | United States |

City | New York |

Period | 22/06/2013 → 27/06/2013 |

Sponsor | ACM SIGMOD |

### Fingerprint

### Keywords

- High-Dimensional Data
- Parallel Coordinates
- Visualization

### Cite this

*Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data*(pp. 1009-1012). Association for Computing Machinery. https://doi.org/10.1145/2463676.2463696

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*Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data.*Association for Computing Machinery, pp. 1009-1012, 2013 ACM SIGMOD Conference on Management of Data, New York, United States, 22/06/2013. https://doi.org/10.1145/2463676.2463696

**Interactive data mining with 3D-parallel-coordinate-trees.** / Achtert, Elke; Kriegel, Hans Peter; Schubert, Erich; Zimek, Arthur.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Interactive data mining with 3D-parallel-coordinate-trees

AU - Achtert, Elke

AU - Kriegel, Hans Peter

AU - Schubert, Erich

AU - Zimek, Arthur

PY - 2013/7/29

Y1 - 2013/7/29

N2 - Parallel coordinates are an established technique to visualize high-dimensional data, in particular for data mining purposes. A major challenge is the ordering of axes, as any axis can have at most two neighbors when placed in parallel on a 2D plane. By extending this concept to a 3D visualization space we can place several axes next to each other. However, finding a good arrangement often does not necessarily become easier, as still not all axes can be arranged pairwise adjacently to each other. Here, we provide a tool to explore complex data sets using 3D-parallel-coordinate-trees, along with a number of approaches to arrange the axes.

AB - Parallel coordinates are an established technique to visualize high-dimensional data, in particular for data mining purposes. A major challenge is the ordering of axes, as any axis can have at most two neighbors when placed in parallel on a 2D plane. By extending this concept to a 3D visualization space we can place several axes next to each other. However, finding a good arrangement often does not necessarily become easier, as still not all axes can be arranged pairwise adjacently to each other. Here, we provide a tool to explore complex data sets using 3D-parallel-coordinate-trees, along with a number of approaches to arrange the axes.

KW - High-Dimensional Data

KW - Parallel Coordinates

KW - Visualization

U2 - 10.1145/2463676.2463696

DO - 10.1145/2463676.2463696

M3 - Article in proceedings

AN - SCOPUS:84880525271

SN - 978-1-4503-2037-5

SP - 1009

EP - 1012

BT - Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data

PB - Association for Computing Machinery

ER -