The dynamic development of information fusion research implies introduction of new terms and concepts, which in turn requires tools and methods for terminology organization and standardization, as well as tools for creating domain-specific ontology. In this paper, we show how natural language processing and corpus technology tools applied for term extraction from texts in biomedicine can successfully be used for the field of information fusion. We demonstrate term and information extraction from a corpus of research articles in information fusion, showing how a vision of a combined text retrieval and information extraction service can be made real.