Our research aims at interactive document viewers that can select and highlight relevant text passages on demand. Another related objective is the generation of topic-specific summaries of texts as opposed to general purpose summaries. This paper introduces our notions of discourse structure tree and level-of-detail tree. Both structures are used to represent relevant aspects of a text segment for the above mentioned purposes. Furthermore, we introduce a Knowledge Acquisition Framework for DIScourse processing (KAFDIS) that allows the incremental and efficient acquisition of knowledge for the reliable construction of the discourse structure graph and the level-of-detail tree based on cue phrases. An effective knowledge acquisition process is crucial to allow the economical development of systems that can handle a large variety of topics. Our knowledge acquisition approach ensures always a consistent knowledge base whose semantics are well controlled by the expert. It is an increment...
Achim G. Hoffmann, Son Bao Pham