Automatic interpretation of natural language for a multimedia e-learning tool

Abstract

This paper describes the new e-learning tool CHESt that allows students to search in a knowledge base for short (teaching) multimedia clips by using a semantic search engine. We explain the different steps to automatically describe the meaning of the clips with RDF (Resource Description Framework). The concept is based on graph theory and retrieval algorithms. Finally, we present rules how a human question can be transformed into a RDF query. Thus, the knowledge base and the query have the same format and can be compared.