The empty family satisfies the bound, so assume is nonempty and choose a graph according to the uniform distribution on a finite set . Let be its random vector of edge indicators, indexed by . Then its information entropy is .
For each vertex , put , so records the graph neighbourhood of . The possible graph neighbourhoods form an intersecting family of subsets of : the graph intersection of any two members of has no isolated vertex at . A subset and its complement cannot both occur. Pairing the subsets into complementary pairs gives at most possible graph neighbourhoods. The maximum entropy on a finite alphabet therefore gives
This argument applies for . For the assumed nonempty family cannot exist, since its only possible graph has an isolated vertex.
Each edge belongs to exactly two of the sets . To obtain the needed instance of Shearer inequality directly from the preceding compression argument, repeatedly apply a union-intersection compression to incomparable members of the multiset . Each such step strictly increases , by
The potential is bounded and integer-valued, so the process terminates in a chain under inclusion. Coordinate multiplicities stay equal to two, so, for , the terminal chain consists of two copies of and empty sets. The compression of an entropy sum now gives
Exponentiating proves the entropy bound for graphs with isolated-vertex-free intersections: