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Chapter 6 , even if this small community is embedded in a much larger graph. That is, we
can treat all nodes in the entire graph as baskets and as items, and run A-priori or one of its
improvements on the entire graph, looking for sets of t items with support s .
EXAMPLE 10.13 Suppose there is a community with 100 nodes on each side, and the aver-
age degree of nodes is 50; i.e., half the possible edges exist. This community will have an
instance of K s,t , provided 100(1/2) t s . For example, if t = 2, then s can be as large as 25.
If t = 3, s can be 11, and if t = 4, s can be 6.
Unfortunately, the approximation we made gives us a bound on s that is a little too high.
If we revert to the original formula
we see that for the case t = 4 we need
That
is,
The expression on the left is not 6, but only 5.87. However, if the average support for an
itemset of size 4 is 5.87, then it is impossible that all those itemsets have support 5 or less.
Thus, we can be sure that at least one itemset of size 4 has support 6 or more, and an in-
stance of K 6 . 4 exists in this community.
10.3.5
Exercises for Section 10.3
EXERCISE 10.3.1 For the running example of a social network from Fig. 10.1 , how many
instances of K s,t are there for:
(a) s = 1 and t = 3.
(b) s = 2 and t = 2.
(c) s = 2 and t = 3.
EXERCISE 10.3.2 Suppose there is a community of 2 n nodes. Divide the community into
two groups of n members, at random, and form the bipartite graph between the two groups.
Suppose that the average degree of the nodes of the bipartite graph is d . Find the set of
maximal pairs ( t, s ), with t s , such that an instance of K s,t is guaranteed to exist, for the
following combinations of n and d :
(a) n = 20 and d = 5.
(b) n = 200 and d = 150.
(c) n = 1000 and d = 400.
By “maximal,” we mean there is no different pair ( s ′, t ′) such that both s ′ ≥ s and t ′ ≥ t hold.
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