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Enterprise Search (ES) is different from traditional IR due to a number of reasons, among which the high level of ambiguity of terms in queries and documents and existence of graph-structured enterprise data (ontologies) that describe the concepts of interest and their relationships to each other, are the most important ones. Our method identifies concepts from the enterprise ontology in the query and corpus. We propose a ranking scheme for ontology sub-graphs on top of approximately matcheddoi:10.1145/1772690.1772709 dblp:conf/www/BrauerHHLNB10 fatcat:tnqxhod4vnfwtkgxu3hwl7ilhi