demonstration

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

Authors:

Hans-Peter Kriegel,

Erich Schubert,

Arthur ZimekAuthors Info & Claims

SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data

Pages 1009 - 1012

https://doi.org/10.1145/2463676.2463696

Published: 22 June 2013 Publication History

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.

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Cited By

Zuo ZLi ZCheng PZhao J(2023)A novel subspace outlier detection method by entropy-based clustering algorithmScientific Reports10.1038/s41598-023-42261-413:1Online publication date: 15-Sep-2023
https://doi.org/10.1038/s41598-023-42261-4
Blumenschein MZhang XPomerenke DKeim DFuchs J(2020)Evaluating Reordering Strategies for Cluster Identification in Parallel CoordinatesComputer Graphics Forum10.1111/cgf.1400039:3(537-549)Online publication date: 18-Jul-2020
https://doi.org/10.1111/cgf.14000
Riahi FSchulte O(2020)Model-based exception mining for object-relational dataData Mining and Knowledge Discovery10.1007/s10618-020-00677-wOnline publication date: 19-Feb-2020
https://doi.org/10.1007/s10618-020-00677-w
Show More Cited By

Index Terms

Interactive data mining with 3D-parallel-coordinate-trees
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data

June 2013

1322 pages

ISBN:9781450320375

DOI:10.1145/2463676

General Chairs:
Kenneth Ross
Columbia University
,
Divesh Srivastava
AT&T Research
,
Program Chair:
Dimitris Papadias
HKUST

Copyright © 2013 ACM.

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 June 2013

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SIGMOD/PODS'13

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SIGMOD

SIGMOD/PODS'13: International Conference on Management of Data

June 22 - 27, 2013

New York, New York, USA

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SIGMOD '13 Paper Acceptance Rate 76 of 372 submissions, 20%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Zuo ZLi ZCheng PZhao J(2023)A novel subspace outlier detection method by entropy-based clustering algorithmScientific Reports10.1038/s41598-023-42261-413:1Online publication date: 15-Sep-2023
https://doi.org/10.1038/s41598-023-42261-4
Blumenschein MZhang XPomerenke DKeim DFuchs J(2020)Evaluating Reordering Strategies for Cluster Identification in Parallel CoordinatesComputer Graphics Forum10.1111/cgf.1400039:3(537-549)Online publication date: 18-Jul-2020
https://doi.org/10.1111/cgf.14000
Riahi FSchulte O(2020)Model-based exception mining for object-relational dataData Mining and Knowledge Discovery10.1007/s10618-020-00677-wOnline publication date: 19-Feb-2020
https://doi.org/10.1007/s10618-020-00677-w
Ding KLi JLiu HCulpepper JMoffat ABennett PLerman K(2019)Interactive Anomaly Detection on Attributed NetworksProceedings of the Twelfth ACM International Conference on Web Search and Data Mining10.1145/3289600.3290964(357-365)Online publication date: 30-Jan-2019
https://dl.acm.org/doi/10.1145/3289600.3290964
Cui W(2019)Visual Analytics: A Comprehensive OverviewIEEE Access10.1109/ACCESS.2019.29237367(81555-81573)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2923736
Sand CLechler TSchuh PFranke J(2018)Potentials for Error Detection and Process Visualization in Assembly Lines Using a Parallel Coordinates PlotApplied Mechanics and Materials10.4028/www.scientific.net/AMM.882.10882(10-16)Online publication date: Jul-2018
https://doi.org/10.4028/www.scientific.net/AMM.882.10
Schubert EGertz MSacharidis DGamper JBöhlen M(2018)Numerically stable parallel computation of (co-)varianceProceedings of the 30th International Conference on Scientific and Statistical Database Management10.1145/3221269.3223036(1-12)Online publication date: 9-Jul-2018
https://dl.acm.org/doi/10.1145/3221269.3223036
Huang XSong QLi JHu XChang YZhai CLiu YMaarek Y(2018)Exploring Expert Cognition for Attributed Network EmbeddingProceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159655(270-278)Online publication date: 2-Feb-2018
https://dl.acm.org/doi/10.1145/3159652.3159655
Bandaragoda TTing KAlbrecht DLiu FZhu YWells J(2018)Isolation‐based anomaly detection using nearest‐neighbor ensemblesComputational Intelligence10.1111/coin.1215634:4(968-998)Online publication date: 5-Jan-2018
https://doi.org/10.1111/coin.12156
Okada Y(2018)Time-Tunnel: 3D Visualization Tool and Its Aspects as 3D Parallel Coordinates2018 22nd International Conference Information Visualisation (IV)10.1109/iV.2018.00019(50-55)Online publication date: Jul-2018
https://doi.org/10.1109/iV.2018.00019
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