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
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.
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