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Ontology-based data mining in digital libraries

Authorized Users Only
2009
Authors
Kovačević, Ana
Conference object (Published version)
Metadata
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Abstract
The paper proposes matching short forms (abbreviated titles from the citation report) with their corresponding longer ones (journal titles in the digital library). The main problem is that there are often a number of syntactically different abbreviated forms for one abbreviated title in the citation report. We use character- and token-based similarity metrics to identify duplicate records. Also, we improve the process of identifying syntactically different data with the automated discovery of ontological knowledge representations such as thesauri from correctly matched data.
Keywords:
ontologies / data mining / digital libraries
Source:
Web 2.0 & Semantic Web, 2009, 163-175
Publisher:
  • Boston : Springer
Note:
  • Annals of Information Systems, vol. 6

DOI: 10.1007/978-1-4419-1219-0_7

ISBN: 978-1-4419-1218-3

[ Google Scholar ]
URI
https://rhinosec.fb.bg.ac.rs/handle/123456789/58
Collections
  • Radovi istraživača
Institution/Community
FB
TY  - CONF
AU  - Kovačević, Ana
PY  - 2009
UR  - https://rhinosec.fb.bg.ac.rs/handle/123456789/58
AB  - The paper proposes matching short forms (abbreviated titles from the citation report) with their corresponding longer ones (journal titles in the digital library). The main problem is that there are often a number of syntactically different abbreviated forms for one abbreviated title in the citation report. We use character- and token-based similarity metrics to identify duplicate records. Also, we improve the process of identifying syntactically different data with the automated discovery of ontological knowledge representations such as thesauri from correctly matched data.
PB  - Boston : Springer
C3  - Web 2.0 & Semantic Web
T1  - Ontology-based data mining in digital libraries
SP  - 163
EP  - 175
DO  - 10.1007/978-1-4419-1219-0_7
UR  - conv_652
ER  - 
@conference{
author = "Kovačević, Ana",
year = "2009",
abstract = "The paper proposes matching short forms (abbreviated titles from the citation report) with their corresponding longer ones (journal titles in the digital library). The main problem is that there are often a number of syntactically different abbreviated forms for one abbreviated title in the citation report. We use character- and token-based similarity metrics to identify duplicate records. Also, we improve the process of identifying syntactically different data with the automated discovery of ontological knowledge representations such as thesauri from correctly matched data.",
publisher = "Boston : Springer",
journal = "Web 2.0 & Semantic Web",
title = "Ontology-based data mining in digital libraries",
pages = "163-175",
doi = "10.1007/978-1-4419-1219-0_7",
url = "conv_652"
}
Kovačević, A.. (2009). Ontology-based data mining in digital libraries. in Web 2.0 & Semantic Web
Boston : Springer., 163-175.
https://doi.org/10.1007/978-1-4419-1219-0_7
conv_652
Kovačević A. Ontology-based data mining in digital libraries. in Web 2.0 & Semantic Web. 2009;:163-175.
doi:10.1007/978-1-4419-1219-0_7
conv_652 .
Kovačević, Ana, "Ontology-based data mining in digital libraries" in Web 2.0 & Semantic Web (2009):163-175,
https://doi.org/10.1007/978-1-4419-1219-0_7 .,
conv_652 .

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