Large amounts of data in many disciplines are continuously being added to semantic or non-semantic web repositories as a result of continuing research in different scientific fields, and it is becoming an increasing challenge for researchers to use these repositories efficiently and at the same time cope with this fast pace of the introduction of new knowledge [5]. It is critical to provide an easy to use querying capability for experts of different fields, especially who like to pose cross-discipline queries on these repositories. In this paper, we present a hybrid natural language question answering system (SemanticQA) on scientific linked data sets (i.e. populated ontologies) as well as scientific literature in the form of publications
سمير الترتير | Samir Tartir | 4696