TESI DOCTORAL - La Salle

E.2. InternetAds data set
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Figure E.8: φ (NMI) boxplots of the self-refined intermodal consensus clustering solutions
using the rb-cos-i2 algorithm on the CAL500 data set.
E.2 InternetAds data set
In the following paragraphs, the results corresponding to the execution of self-refining multimodal
consensus clustering on the InternetAds collection are presented. In this case, the
modalities are object (i.e image) attributes and collateral image attributes (see appendix
A.2.2 for a description).
E.2.1 Consensus clustering per modality and across modalities
In this section, the quality of the unimodal, multimodal and intermodal consensus clusterings
obtained on the cluster ensembles generated upon the agglo-cos-upgma, direct-cos-i2,
graph-cos-i2 and rb-cos-i2 clustering algorithms is evaluated.
Firstly, the results corresponding to the agglo-cos-upgma cluster ensemble are depicted
in figure E.9. The first thing to notice is the extremely low quality of the cluster ensemble
components, regardless of the modality. This fact conditions the consensus clustering results
obtained, which are also of very low quality. Moreover, in contrast to what has been observed
in the rest of experiments, there exist very little differences among the performance of the
distinct consensus functions employed.
A very similar behaviour is observed in the experiments conducted on the direct-cos-i2
and rb-cos-i2 cluster ensembles (figures E.10 and E.12). However, pretty different results are
obtained on the graph-cos-i2 cluster ensemble (see figure E.11). In this case, the execution
of consensus clustering on the collateral and the multimodal modalities yields better results.
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