Cluster analysis using similarity proximity (count) data as input

*(Q) How could we cluster about 60 photos (Hierarchical Cluster) once all the
photos are sorted into 10 groups based their similarity with each other
by 100 participants. For example, about 6 times Photo A was put
together with Photo B in the sample data below. 

How can one use that type of similarity proximity (count) data
as input and get the dendogram and cluster membership as OUPUT?

*(A) posted to SPSSX-L list on 2001/10/12 by Jelani Mandara.

DATA LIST FREE /ROWTYPE_(a8) VARNAME_(a8) a b c d e f g h i j.
BEGIN DATA
PROX     A    0 6 2 7 18 0 1 5 9 14
PROX     B    6 0 14 3 8 4 19 14 11 1
PROX     C    2 14 0 30 12 4 6 8 19 10
PROX     D    7 3 30 0 1 16 3 4 8 11
PROX     E    18 8 12 1 0 19 13 14 10 9
PROX     F    0 4 4 16 19 0 5 1 14 1
PROX     G    1 19 6 3 13 5 0 16 3 1
PROX     H    5 14 8 4 14 1 16 0 11 1
PROX     I    9 11 19 8 10 14 3 11 0 9
PROX     J   14 1 10 11 9 1 1 1 9 0
END DATA.
EXECUTE.

SAVE OUTFILE='C:\\temp\\photoproximities.sav'.

CLUSTER
  /MATRIX IN  ('C:\\temp\\photoproximities.sav')
  /METHOD BAVERAGE
  /PRINT CLUSTER(2,8)
  /PRINT SCHEDULE
  /PRINT DISTANCE
  /PLOT DENDROGRAM VICICLE.