In this paper we present i) an approach for clustering authors according to their citation distributions and ii) an ontology, the Bibliometric Data Ontology, for supporting the formal representation of such clusters. This method allows the formulation of queries which take in consideration the citation behaviour of an author and predicts with a good level of accuracy future citation behaviours. We evaluate our approach with respect to alternative solutions and discuss the predicting abilities of the identified clusters.

Osborne, F., Peroni, S., & Motta, E. (2014). Clustering citation distributions for semantic categorization and citation prediction. In 4th Workshop on Linked Science: Making Sense Out of Data, LISC 2014, Collocated with the 13th International Semantic Web Conference, ISWC 2014 (pp.24-35). CEUR-WS.

Clustering citation distributions for semantic categorization and citation prediction

Osborne F;
2014

Abstract

In this paper we present i) an approach for clustering authors according to their citation distributions and ii) an ontology, the Bibliometric Data Ontology, for supporting the formal representation of such clusters. This method allows the formulation of queries which take in consideration the citation behaviour of an author and predicts with a good level of accuracy future citation behaviours. We evaluate our approach with respect to alternative solutions and discuss the predicting abilities of the identified clusters.
Si
paper
Scientifica
Bibliometric data; BiDO; Data mining; Expert search; Hierarchical clustering; OWL; RDF; Research data; Semantic web; SPARQL;
English
4th Workshop on Linked Science: Making Sense Out of Data, LISC 2014, Collocated with the 13th International Semantic Web Conference, ISWC 2014
Osborne, F., Peroni, S., & Motta, E. (2014). Clustering citation distributions for semantic categorization and citation prediction. In 4th Workshop on Linked Science: Making Sense Out of Data, LISC 2014, Collocated with the 13th International Semantic Web Conference, ISWC 2014 (pp.24-35). CEUR-WS.
Osborne, F; Peroni, S; Motta, E
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/381583
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