English

Abstract

In this paper we present an e-librarian service which is able to retrieve multimedia resources from a knowledge base in a more efficient way than by browsing through an index or by using a simple keyword search. We explored the approach to allow the user to formulate a complete question in natural language. Our background theory is composed of three steps. Firstly, there is the linguistic pre-processing of the user question. Secondly, there is the semantic interpretation of the user question into a logical and unambiguous form, i.e. \(\mathcal{ALC}\) terminology. The focus function resolves ambiguities in the question; it returns the best interpretation for a given word in the context of the complete user question. Thirdly, there is the generation of a semantic query, and the retrieval of pertinent documents. We developed two prototypes: one about computer history (CHESt), and one about fractions in mathematics (MatES). We report on experiments with these prototypes that confirm the feasibility, the quality and the benefits of such an e-librarian service. From 229 different user questions, the system returned for 97% of the questions the right answer, and for nearly half of the questions only one answer, the best one.