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Serge Linckels, Christoph Meinel
Semantic Interpretation of Natural Language User Input to Improve Search in Multimedia Knowledge Base
Keywords: digital libraries, e-Learning, semantic search engine, natural language, information retrieval
In this article 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. Our premise is that more pertinent results would be retrieved if the e-librarian service had a semantic search engine which understood the sense of the user´s query. We explored the approach to allow the user to formulate a complete question in natural language. We present our background theory, which 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., ALC terminology. Thirdly, there is the generation of a semantic query, and the retrieval of pertinent documents. The background theory was implemented in two prototypes. We report on experiments 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 answer, and for nearly half of the questions only one answer (the best one).
it – Information Technology (vormals it+ti), Oldenbourg Wissenschaftsverlag
Print ISSN: 1611-2776
Volume: 49, 01/2007
Pages: 40 - 48