  We introduce a method to find network motifs in knowledge graphs. Network
motifs are useful patterns or meaningful subunits of the graph that recur
frequently. We extend the common definition of a network motif to coincide with
a basic graph pattern. We introduce an approach, inspired by recent work for
simple graphs, to induce these from a given knowledge graph, and show that the
motifs found reflect the basic structure of the graph. Specifically, we show
that in random graphs, no motifs are found, and that when we insert a motif
artificially, it can be detected. Finally, we show the results of motif
induction on three real-world knowledge graphs.
