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Summary: Automatic indexing of documents with ontologies
Anjo Anjewierden and Suzanne Kabel
Social Science Informatics, University of Amsterdam
Roetersstraat 15, 1018 WB Amsterdam, The Netherlands
email: \{anjo,kabel\}@swi.psy.uva.nl
Abstract
Indexing large bodies of data is necessary to enable satisfactory search results.
Ontologies serve as fixed vocabularies to index data from different viewpoints. We
describe how AIDAS, a software tool, automatically divides the source data (PDF doc-
uments) into reusable chunks, how it automatically indexes these chunks and stores
them in a database to enable reuse.
1 Introduction
A large body of knowledge is available as formatted text written with a particular purpose
in mind. One example of such bodies of text are technical manuals. These manuals con-
tain all information about a particular system or device, such as a helicopter, as viewed
from the manufacturer (reference and maintenance). Reusing these manuals for instruc-
tional purposes requires a different perspective on the content of the material and often
also a more attractive presentation.
In this paper we describe our approach to partially automating the process of indexing
technical manuals such that an author of training material can retrieve the appropriate
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