Name
Abstract | ||
|---|---|---|
There exist many methods for deriving music similarity as- sociations and additional variations are likely to be seen in the future. In this work we introduce the Similarity Ontology for describing associations between items. Us- ing a combination of RDF/OWL and N3, our ontology al- lows for transparency and provenance tracking in a dis- tributed and open system. We describe a similarity ecosys- tem where agents assert and aggregate similarity statements on the Web of Data allowing a client application to make queries for recommendation, playlisting, or other tasks. In this ecosystem any number of similarity derivation meth- ods can exist side-by-side, specifying similarity relation- ships as well as the processes used to derive these state- ments. The data consumer can then select which similarity statements to trust based on knowledge of the similarity derivation processes or a list of trusted assertion agents. |
Year | Venue | Keywords |
|---|---|---|
2009 | ISMIR 2013 | web of data,open system |
Field | DocType | Citations |
Semantic similarity,Transparency (graphic),Ontology,Information retrieval,Computer science,Assertion,Similarity heuristic,Normalized compression distance,Open system (systems theory),RDF | Conference | 10 |
PageRank | References | Authors |
1.34 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kurt Jacobson | 1 | 47 | 4.66 |
| Yves Raimond | 2 | 373 | 45.93 |
| Mark Sandler | 3 | 102 | 9.81 |