Name
Title | ||
|---|---|---|
A deductive approach to the identification and description of clusters in Linked Open Data. |
Abstract | ||
|---|---|---|
We propose an approach for inferring clusters in collections of RDF resources based on the features shared by their descriptions. The approach grounds on an algorithm for computing Common Subsumers in RDF proposed in a previous research work. The clustering service introduced here returns not only a possible partition of resources in a collection, but also a description of the knowledge shared within each cluster, in terms of (generalized) RDF triples. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3233/978-1-61499-419-0-987 | Frontiers in Artificial Intelligence and Applications |
Field | DocType | Volume |
Cluster (physics),Computer science,Linked data,Theoretical computer science,Cluster analysis,Partition (number theory),RDF Schema,RDF | Conference | 263 |
ISSN | Citations | PageRank |
0922-6389 | 2 | 0.37 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simona Colucci | 1 | 1047 | 71.96 |
| Silvia Giannini 0001 | 2 | 27 | 3.38 |
| Francesco M. Donini | 3 | 3481 | 452.47 |
| Eugenio Di Sciascio | 4 | 1733 | 147.71 |