Historically, information retrieval (IR) has followed two principally different paths that we call syntactic IR and semantic IR. In syntactic IR, terms are represented as arbitrary sequences of characters and IR is performed through the computation of string similarity. In semantic IR, instead, terms are represented as concepts and IR is performed through the computation of semantic relatedness between concepts. Semantic IR, in general, demonstrates lower recall and higher precision than syntactic IR. However, so far the latter has definitely been the winner in practical applications. In this paper we present a novel approach which allows it to extend syntactic IR with semantics, thus leverage the advantages of both syntactic and semantic IR. First experimental results, reported in the paper, show that the combined approach performs at least as good as syntactic IR, often improving results where semantics can be exploited.