Linked open knowledge organization systems
Abstract:
The Web is the most used Internet’s service to create and share information. In large information collections, Knowledge Organization plays a key role in order to classify and to nd valuable information. Likewise, Linked Open Data is a powerful approach for linking dierent Web datasets. Today, several Knowledge Organization Systems are published by using the design criteria of linked data, it facilitates the automatic processing of them. In this paper, we address the issue of traversing open Knowledge Organization Systems, considering diculties associated with their dynamics and size. To ll this issue, we propose a method to identify irrelevant nodes on an open graph, thus reducing the time and the scope of the graph path and maximizing the possibilities of nding more relevant results. The approach for graph reduction is independent of the domain or task for which the open system will be used. The preliminary results of the proof of concept lead us to think that the method can be eective when the coverage of the concept of interest increases.
Año de publicación:
2019
Keywords:
- Rdf
- KOS
- Graph traversing
- dbpedia
- SPARQL
Fuente:

Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Web Semántica
Áreas temáticas:
- Funcionamiento de bibliotecas y archivos
- Biblioteconomía y Documentación informatica