Integrating Guided Clustering in Visual Analytics to Support Domain Expert Reasoning Processes
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Recent research shows promise in combining Information Visualization (IV) and Machine Learning (ML) to assist data analysis performed by domain experts. However, this approach presents non-trivial challenges, in particular when the goal is to incorporate knowledge provided by the domain expert in underlying ML algorithms. To address these challenges, we present an analytical process and a visual analytics tool that uses visual queries to capture examples from the domain experts' existing reasoning process which will guide the subsequent clustering. Our work is motivated by a collaboration with personnel at the Danish Business Authority, who are interested in two types of insights: (1) On which data dimensions is a selected subset of companies different from the remaining companies? (2) Which other companies lie within the same multi-dimensional subspace? The poster will illustrate a real analysis scenario, where the presented analytic process allows auditors to use their knowledge of identified "suspicious" companies to kick-start the analysis for others.
Description
@inproceedings{10.2312:eurp.20171164,
booktitle = {EuroVis 2017 - Posters},
editor = {Anna Puig Puig and Tobias Isenberg},
title = {{Integrating Guided Clustering in Visual Analytics to Support Domain Expert Reasoning Processes}},
author = {Mathisen, Andreas and Nielsen, Matthias and Grønbæk, Kaj},
year = {2017},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-044-4},
DOI = {10.2312/eurp.20171164}
}