This paper presents a practical heuristic algorithm to address a node discovery problem. The node discovery problem is to discover a clue on the person, who does not appear in the observed records, but is relevant functionally in affecting decision-making and behavior of an organization. We define two topological relevance of a node in a social network (global and local relevance). Association between the topological relevance and the functional relevance is studied with a few example networks in criminal organizations. We propose a heuristic algorithm to infer an invisible, functionally relevant person. Its performance (precision, recall, and F value) is demonstrated with a simulation experiment using a network derived from the Watts-Strogatz (WS) model.
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