Image Processing Reference
In-Depth Information
indicated by email affiliations, while phone calls seem to reflect more friendship and family
relations. However, the detected structures are still rather close to each other (cf. columns
in Table 1) reflecting underlaying social affinity. As one can see, by properly combining
information from different graph layers we can improve the reliability of communities
detection.
Fig. 14. Communities detected in the combined BT & phone-calls network and mapped on
the phone-calls network.
NMI
Purity
RI
Q
Phone calls
0.262
0.434
0.698
0.638
BT proximity
0.307
0.456
0.720
0.384
GPS
0.313
0.471
0.704
0.101
Phone + BT
0.342
0.427
0.783
Table 1. Evaluation of community detection in multi-layer graphs.
7.3 Application for recommendation systems
As discussed in Section 4, one of applications of the soft communities detection and coupled
systems dynamics may be seen in recommendation systems. To illustrate the approach we
selected the user "129" (marked by oval) in the phone-calls network at Fig.12 and calculated
proposed prediction scores for different similarity measures.
First,
we
consider
intra-community
predictions
made
by
coupled
dynamical
systems.
=
Fig.15(a) depicts pair-wise correlations (scaled by 5) between oscillators at t
10 for
the sub-network at Fig.12 forming the intra-community of the user "129".
By changing
Search WWH ::




Custom Search