Panning for Insight: Amplifying Insight through Tight Integration of Machine Learning, Data Mining, and Visualization
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Date
2018
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
With the rapid progress made in Data Mining, Visualization, and Machine Learning during the last years, combinations of these methods have gained increasing interest. This paper summarizes ideas behind ongoing work on combining methods of these three domains into an insight-driven interactive data analysis workflow. Based on their interpretation of data visualizations, users generate metadata to be fed back into the analysis. The resulting resonance effect improves the performance of subsequent analysis. The paper outlines the ideas behind the workflow, indicates the benefits and discusses how to avoid potential pitfalls.
Description
@inproceedings{10.2312:mlvis.20181130,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Ian Nabney and Jaakko Peltonen and Daniel Archambault},
title = {{Panning for Insight: Amplifying Insight through Tight Integration of Machine Learning, Data Mining, and Visualization}},
author = {Karer, Benjamin and Scheler, Inga and Hagen, Hans},
year = {2018},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-062-8},
DOI = {10.2312/mlvis.20181130}
}