TESI DOCTORAL - La Salle

Appendix E
Experiments on multimodal
consensus clustering
This appendix presents several experiments regarding multimodal self-refining consensus
architectures described in chapter 5, applied to the CAL500, InternetAds and Corel data
collections. Due to space limitations, the experiments described correspond to the application
of the proposed methodology on cluster ensembles resulting from the application of four
of the twenty-eight clustering algorithms employed in this thesis, namely agglo-cos-upgma,
direct-cos-i2, graph-cos-i2 and rb-cos-i2.
For each one of the data sets, two facets of the experiments are presented separately.
Firstly, the consensus clusterings obtained on each modality and across modalities is qualitatively
evaluated. To do so, a set of boxplot charts displaying the φ (NMI) values of the
components of the corresponding cluster ensemble E, and of the unimodal, multimodal and
intermodal consensus clusterings obtained by the seven consensus functions employed in
this work across 10 independent runs.
And secondly, the quality of the self-refined consensus clustering solutions output by
the proposed consensus self-refining procedure is also evaluated with the help of boxplot
diagrams displaying the φ (NMI) values of the corresponding cluster ensembles, of the nonrefined
consensus clustering λc and of the self-refined consensus clustering solutions λc p i .
As regards the latter, a set of refined clusterings are obtained using a range of percentages
pi = {2, 5, 10, 15, 20, 30, 40, 50, 60, 75} of the whole ensemble E. The performance of the
φ (ANMI) -based supraconsensus function for picking up one of the λc p i is also qualitatively
evaluated.
E.1 CAL500 data set
In this section, the results of the multimodal consensus clustering experiments conducted
on the CAL500 data collection are described. The modalities contained in this data set are
audio and text —see appendix A.2.2 for a description.
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