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VIS4ML: an ontology for visual analytics assisted machine learning

Abstract:

While many VA workflows make use of machine-learned models to support analytical tasks, VA workflows have become increasingly important in understanding and improving Machine Learning (ML) processes. In this paper, we propose an ontology (VIS4ML) for a subarea of VA, namely "VA-assisted ML". The purpose of VIS4ML is to describe and understand existing VA workflows used in ML as well as to detect gaps in ML processes and the potential of introducing advanced VA techniques to such processes. On...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/TVCG.2018.2864838

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Oxford e-Research Centre
Oxford college:
Pembroke College
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
IEEE Transactions on Visualization and Computer Graphics Journal website
Volume:
25
Issue:
1
Pages:
385 - 395
Publication date:
2018-08-17
Acceptance date:
2018-07-11
DOI:
EISSN:
1941-0506
ISSN:
1077-2626
Source identifiers:
911446
Pubs id:
pubs:911446
UUID:
uuid:5568f4b5-952f-48c5-89e3-9ab10043a931
Local pid:
pubs:911446
Deposit date:
2018-10-02

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