A HYBRID APPROACH TOWARDS INFORMATION EXPANSION BASED ON SHALLOW AND DEEP METADATA

Tudor Groza, Siegfried Handschuh

2009

Abstract

The exponential growth of the World Wide Web in the last decade, brought an explosion in the information space, with important consequences also in the area of scientific research. Lately, finding relevant work in a particular field and exploring links between relevant publications, became a cumbersome task. In this paper we propose a hybrid approach to automatic extraction of semantic metadata from scientific publications that can help to alleviate, at least partially, the above mentioned problem. We integrated the extraction mechanisms in an application targeted to early stage researchers. The application harmoniously combines the metadata extraction with information expansion and visualization for the seamless exploration of the space surrounding scientific publications.

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Paper Citation


in Harvard Style

Groza T. and Handschuh S. (2009). A HYBRID APPROACH TOWARDS INFORMATION EXPANSION BASED ON SHALLOW AND DEEP METADATA . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2009) ISBN 978-989-674-012-2, pages 109-116. DOI: 10.5220/0002271001090116

in Bibtex Style

@conference{keod09,
author={Tudor Groza and Siegfried Handschuh},
title={A HYBRID APPROACH TOWARDS INFORMATION EXPANSION BASED ON SHALLOW AND DEEP METADATA},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2009)},
year={2009},
pages={109-116},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002271001090116},
isbn={978-989-674-012-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2009)
TI - A HYBRID APPROACH TOWARDS INFORMATION EXPANSION BASED ON SHALLOW AND DEEP METADATA
SN - 978-989-674-012-2
AU - Groza T.
AU - Handschuh S.
PY - 2009
SP - 109
EP - 116
DO - 10.5220/0002271001090116