Ontology-based data mining in digital libraries
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 librariesSource:
Web 2.0 & Semantic Web, 2009, 163-175Publisher:
- Boston : Springer
Note:
- Annals of Information Systems, vol. 6
Collections
Institution/Community
FBTY - 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 .