Automatic metadata generation by utilising pre-existing metadata of related resources

Authors:
Merkourios Margaritopoulos;Thomas Margaritopoulos;Isabella Kotini;Athanasios Manitsaris
Affiliations:
Department of Applied Informatics, University of Macedonia, 156 Egnatia Street, 54006, Thessaloniki, Greece.;Department of Applied Informatics, University of Macedonia, 156 Egnatia Street, 54006, Thessaloniki, Greece.;Department of Applied Informatics, University of Macedonia, 156 Egnatia Street, 54006, Thessaloniki, Greece.;Department of Applied Informatics, University of Macedonia, 156 Egnatia Street, 54006, Thessaloniki, Greece
Venue:
International Journal of Metadata, Semantics and Ontologies
Year:
2008

Citing 9
Cited 0

Automatic metadata generation & evaluation

SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Meta-information for multimedia elearning

Computer Science in Perspective
On the Semantics of Aggregation and Generalization in Learning Object Contracts

ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Automating metadata generation: the simple indexing interface

WWW '05 Proceedings of the 14th international conference on World Wide Web
Functionalities for automatic metadata generation applications: a survey of metadata experts' opinions

International Journal of Metadata, Semantics and Ontologies
Complete metadata records in learning object repositories: some evidence and requirements

International Journal of Learning Technology
Making metadata go away: "hiding everything but the benefits"

DCMI '04 Proceedings of the 2004 international conference on Dublin Core and metadata applications: metadata across languages and cultures
A conceptual framework for metadata quality assessment

DCMI '08 Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications
Relation-based heuristic diffusion framework for LOM generation

Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

Manual indexing of digital resources according to metadata standards is a laborious task. Methods and methodologies for automatically producing several parts of a resource's metadata provide valuable assistance to indexers and cataloguers by reducing the burden of their manual work. A methodology, which aims at identifying inference rules for the automatic generation of a resource's metadata, based on pre-existing metadata of its related resources, is introduced in this paper. Furthermore, the application of the methodology to the IEEE LOM standard and an experimental example on a working database of metadata, with a tool developed for this purpose, are demonstrated.