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Fishgram, a novel algorithm for recognizing frequent or otherwise interesting sub-hypergraphs in large, heterogeneous hypergraphs, is presented. The algorithm's implementation the OpenCog integrative AGI framework is described, and concrete examples are given showing the patterns it recognizes in OpenCog's hypergraph knowledge store when the OpenCog system is used to control a virtual agent in a game world. It is argued that Fishgram is well suited to fill a critical niche in OpenCog and potentially other integrative AGI architectures: scalable recognition of relatively simple patterns in heterogeneous, potentially rapidly-changing data.