Abstract: A scalable infrastructure for searching multiple disparate textual databases by mapping their contents onto a structured ontology, e.g., of medical concepts. This framework can be leveraged against any database where free-text attributes are used to describe the constituent records.

Abstract: A method of computing a measure of similarity between nodes of first and second networks is described. In particular, sets of pairwise scores are computed to find nodes in the individual networks that are good matches to one another. Thus, a pairwise score, referred to as Rij, is computed for a node i in the first network and a node j in the second network. Similar pairwise scores are computed for each of the nodes in each network. The goal of this process is to identify node pairs that exhibit high Rij values. According to the technique described herein, the intuition is that nodes i and j are a good match if their neighbors are a good match. This technique produces a measure of “network similarity.” If node feature data also is available, the intuition may be expanded such that nodes i and j are considered a good match if their neighbors are a good match (network similarity) and their node features are a good match (node similarity). Node feature data typically is domain-specific.