Can Feature Information Interaction Help for Information Fusion in Multimedia Problems?

Jana Kludas, Eric Bruno, Stephane Marchand-Maillet



The article presents the information-theoretic based feature information interaction, a measure that can describe complex feature dependencies in multivariate settings. According to the theoretical development, feature interactions are more accurate than current, bivariate dependence measures due to their stable and unambiguous definition. In experiments with artificial and real data we compare the empirical estimates of correlation, mutual information and 3-way feature interaction. We can conclude that feature interactions give a more detailed and accurate description of data structures that should be exploited for information fusion in multimedia problems.


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Paper Citation

in Harvard Style

Kludas J., Bruno E. and Marchand-Maillet S. (2008). Can Feature Information Interaction Help for Information Fusion in Multimedia Problems? . In Metadata Mining for Image Understanding - Volume 1: MMIU, (VISIGRAPP 2008) ISBN 978-989-8111-24-1, pages 23-33. DOI: 10.5220/0002339500230033

in Bibtex Style

author={Jana Kludas and Eric Bruno and Stephane Marchand-Maillet},
title={Can Feature Information Interaction Help for Information Fusion in Multimedia Problems?},
booktitle={Metadata Mining for Image Understanding - Volume 1: MMIU, (VISIGRAPP 2008)},

in EndNote Style

JO - Metadata Mining for Image Understanding - Volume 1: MMIU, (VISIGRAPP 2008)
TI - Can Feature Information Interaction Help for Information Fusion in Multimedia Problems?
SN - 978-989-8111-24-1
AU - Kludas J.
AU - Bruno E.
AU - Marchand-Maillet S.
PY - 2008
SP - 23
EP - 33
DO - 10.5220/0002339500230033