caa a22 4500 605478562 CHVBK 20210128100406.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s10994-014-5464-x doi (NATIONALLICENCE)springer-10.1007/s10994-014-5464-x Information retrieval approach to meta-visualization [Elektronische Daten] [Jaakko Peltonen, Ziyuan Lin] Visualization is crucial in the first steps of data analysis. In visual data exploration with scatter plots, no single plot is sufficient to analyze complicated high-dimensional data sets. Given numerous visualizations created with different features or methods, meta-visualization is needed to analyze the visualizations together. We solve how to arrange numerous visualizations onto a meta-visualization display, so that their similarities and differences can be analyzed. Visualization has recently been formalized as an information retrieval task; we extend this approach, and formalize meta-visualization as an information retrieval task whose performance can be rigorously quantified and optimized. We introduce a machine learning approach to optimize the meta-visualization, based on an information retrieval perspective: two visualizations are similar if the analyst would retrieve similar neighborhoods between data samples from either visualization. Based on the approach, we introduce a nonlinear embedding method for meta-visualization: it optimizes locations of visualizations on a display, so that visualizations giving similar information about data are close to each other. In experiments we show such meta-visualization outperforms alternatives, and yields insight into data in several case studies. The Author(s), 2014 Meta-visualization nationallicence Neighbor embedding nationallicence Nonlinear dimensionality reduction nationallicence Peltonen Jaakko Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, P.O. Box 15400, FI-00076, Aalto, Finland aut Lin Ziyuan Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, P.O. Box 15400, FI-00076, Aalto, Finland aut Machine Learning Springer US; http://www.springer-ny.com 99/2(2015-05-01), 189-229 0885-6125 99:2<189 2015 99 10994 https://doi.org/10.1007/s10994-014-5464-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10994-014-5464-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Peltonen Jaakko Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, P.O. Box 15400, FI-00076, Aalto, Finland aut NATIONALLICENCE 700 1- Lin Ziyuan Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, P.O. Box 15400, FI-00076, Aalto, Finland aut NATIONALLICENCE 773 0- Machine Learning Springer US; http://www.springer-ny.com 99/2(2015-05-01), 189-229 0885-6125 99:2<189 2015 99 10994