The value of weights in automatically generated text structures

Abstract

One question that arises if we want to evolve generation techniques to accommodate Web ontologies is how to capture and expose the relevant ontology content to the user. This paper presents an attempt to answer the question about how to select the ontology statements that are significant for the user and present those statements in a way that helps the user to learn. Our generation approach combines bottom-up and top-down techniques with enhanced comparison methods to tailor descriptions about a concept described in an ontology. A preliminary evaluation indicates that the process of computing preferable property weights in addition to enhanced generation methods has a positive effect on the text structure and its content. Future work aims to assign grammar rules and lexical entries in order to produce coherent texts that follow on from the generated text structures in several languages. © Springer-Verlag Berlin Heidelberg 2009.