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Extracting domain knowledge from tables of contents

  • Knowledge in textual form is always presented as visually and hierarchically structured units of text, which is particularly true in the case of academic texts. One research hypothesis of the ongoing project Knowledge ordering in texts - text structure and structure visualisations as sources of natural ontologies1 is that the textual structure of academic texts effectively mirrors essential parts of the knowledge structure that is built up in the text. The structuring of a modern dissertation thesis (e.g. in the form of an automatically generated table of contents - toes), for example, represents a compromise between requirements of the text type and the methodological and conceptual structure of its subject-matter. The aim of the project is to examine how visual-hierarchical structuring systems are constructed, how knowledge structures are encoded in them, and how they can be exploited to automatically derive ontological knowledge for navigation, archiving, or search tasks. The idea to extract domain concepts and semantic relations mainly from the structural and linguistic information gathered from tables of contents represents a novel approach to ontology learning.

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Author:Harald LüngenGND, Henning LobinGND
Parent Title (English):Digital Humanities 2010. Conference Abstracts. King’s College London, London July 7 – 10, 2010
Publisher:Office for Humanities Communication; Centre for Computing in the Humanities (King’s College London
Place of publication:London
Document Type:Conference Proceeding
Year of first Publication:2010
Date of Publication (online):2018/07/04
GND Keyword:Ontologie <Wissensverarbeitung>; Semantische Relation; Visualisierung; Wissensrepräsentation
First Page:331
DDC classes:400 Sprache / 430 Deutsch
Open Access?:ja
Licence (German):License LogoCreative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International