Abstract
In this paper, we outline an ontology-driven approach to the organisation, classification, and mining of cultural heritage documents on the Semantic Web. We propose its implementation as a person-machine system that uses Statistical NLP methods to extract cultural heritage information from texts contained in distributed information sources connected within a schema-based peer-to-peer network infrastructure.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Doerr, M., Stead, S., et al.: Definition of the CIDOC CRM, http://cidoc.ics.forth.gr/
Finn, N.: Kushmerick. Active learning strategies for information extraction. In: Proceedings of the ECML/PKDD Workshop on ATEM, Cavtat-Dubrovnik, Croatia (September 2003)
Nejdl, W., et al.: Super-peer-based routing and clustering strategies for RDF-based peer-topeer networks. In: Proceedings of WWW 2003, Budapest, Hungary (May 2003)
Papadopoulos, D.C., Mavrikas, E.C.: Peer-to-peer ways to Cultural Heritage. In: Proceedings of CAA 2003, Vienna, Austria (April 2003)
Project JXTA, http://www.jxta.org/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mavrikas, E.C., Nicoloyannis, N., Kavakli, E. (2004). Cultural Heritage Information on the Semantic Web. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds) Engineering Knowledge in the Age of the Semantic Web. EKAW 2004. Lecture Notes in Computer Science(), vol 3257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30202-5_35
Download citation
DOI: https://doi.org/10.1007/978-3-540-30202-5_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23340-4
Online ISBN: 978-3-540-30202-5
eBook Packages: Springer Book Archive