loading
Documents

Research.Publish.Connect.

Paper

Authors: Jaakko Peltonen and Ziyuan Lin

Affiliation: Aalto University and University of Tampere, Finland

ISBN: 978-989-758-228-8

Keyword(s): Parallel Coordinates, Visualization, Machine Learning, Dimensionality Reduction.

Related Ontology Subjects/Areas/Topics: Abstract Data Visualization ; Computer Vision, Visualization and Computer Graphics ; General Data Visualization ; High-Dimensional Data and Dimensionality Reduction ; Information and Scientific Visualization ; Visual Data Analysis and Knowledge Discovery

Abstract: Parallel Coordinate Plots (PCPs) are a prominent approach to visualize the full feature set of high-dimensional vectorial data, either standalone or complementing other visualizations like scatter plots. Optimization of PCPs has concentrated on ordering and positioning of the coordinate axes based on various statistical criteria. We introduce a new method to construct PCPs that are directly optimized to support a common data analysis task: analyzing neighborhood relationships of data items within each coordinate axis and across the axes. We optimize PCPs on 1D lines or 2D planes for accurate viewing of neighborhood relationships among data items, measured as an information retrieval task. Both the similarity measurement between axes and the axis positions are directly optimized for accurate neighbor retrieval. The resulting method, called Parallel Coordinate Plots for Neighbor Retrieval (PCP-NR), achieves better information retrieval performance than traditional PCPs in experiments.

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.198.142.121

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Peltonen J. and Lin Z. (2017). Parallel Coordinate Plots for Neighbor Retrieval.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017) ISBN 978-989-758-228-8, pages 40-51. DOI: 10.5220/0006097400400051

@conference{ivapp17,
author={Jaakko Peltonen and Ziyuan Lin},
title={Parallel Coordinate Plots for Neighbor Retrieval},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)},
year={2017},
pages={40-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006097400400051},
isbn={978-989-758-228-8},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, (VISIGRAPP 2017)
TI - Parallel Coordinate Plots for Neighbor Retrieval
SN - 978-989-758-228-8
AU - Peltonen J.
AU - Lin Z.
PY - 2017
SP - 40
EP - 51
DO - 10.5220/0006097400400051

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.