TESI DOCTORAL - La Salle

φ (NMI)
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image
λ direct−cos−i2
c
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CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(a) Modality 1
φ (NMI)
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Chapter 5. Multimedia clustering based on cluster ensembles
speech
λ direct−cos−i2
c
E
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(b) Modality 2
φ (NMI)
image+speech
λ direct−cos−i2
c
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E
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(c) Multimodal
φ (NMI)
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λ c direct−cos−i2
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CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(d) Intermodal
Figure 5.4: φ (NMI) boxplots of the unimodal, multimodal and intermodal consensus clustering
solutions using the direct-cos-i2 algorithm on the IsoLetters data set.
φ (NMI)
1
0.8
0.6
0.4
0.2
0
image
λ graph−cos−i2
c
E
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(a) Modality 1
φ (NMI)
1
0.8
0.6
0.4
0.2
0
speech
λ graph−cos−i2
c
E
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(b) Modality 2
φ (NMI)
image+speech
λ graph−cos−i2
c
1
0.8
0.6
0.4
0.2
0
E
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(c) Multimodal
φ (NMI)
1
0.8
0.6
0.4
0.2
0
λ c graph−cos−i2
E
CSPA
EAC
HGPA
MCLA
ALSAD
KMSAD
SLSAD
(d) Intermodal
Figure 5.5: φ (NMI) boxplots of the unimodal, multimodal and intermodal consensus clustering
solutions using the graph-cos-i2 algorithm on the IsoLetters data set.
of the data (λ image+speech
c ) attain a higher quality than any of their unimodal counterparts
(a 16.1% better in relative terms). Moreover, intermodal consensus –figure 5.5(d)– gives
rise to clusterings that, at best, are comparable to the partitions obtained on the multimodal
modality (e.g. ALSAD and KMSAD, where average relative φ (NMI) losses of 3% are
observed) and, in the worst cases, constitute a trade-off between the combined modalities.
Last, notice that pretty similar results are obtained when this consensus process is applied
on the cluster ensemble created by the compilation of the partitions output by the
rb-cos-i2 CLUTO clustering algorithm (see figure 5.6). Once more, the comparison of the
consensus clusterings obtained on the unimodal and multimodal modalities (figures 5.6(a)
to 5.6(c)) reveals the superiority of the latter on this data collection. When these three
modalities are fused in the final consensus stage of the DHCA, the obtained intermodal
consensus clustering solution λc yielded by the CSPA, ALSAD, KMSAD and SLSAD consensus
functions attain φ (NMI) values only 0.9% to a 7.1% worse than those attained on the
multimodal data representation, as depicted in figure 5.6(d).
While the boxplots depicted in figures 5.3 to 5.6 provide the reader with a qualitative
though partial vision of the results of unimodal, multimodal and intermodal consensus
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