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| DOI | 10.1145/3184558.3191646 | ||||
| Año | 2018 | ||||
| Tipo | proceedings paper |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
Despite its importance to the Web, multimedia content is often neglected when building and designing knowledge-bases: though descriptive metadata and links are often provided for images, video, etc., the multimedia content itself is often treated as opaque and is rarely analysed. IMGPEDIA is an effort to bring together the images of WIKIMEDIA COMMONS (including visual information), and relevant knowledge-bases such as WIKIDATA and DBPEDIA. The result is a knowledge-base that incorporates similarity relations between the images based on visual descriptors, as well as links to the resources of WIKIDATA and DBPEDIA that relate to the image. Using the IMGPEDIA SPARQL endpoint, it is then possible to perform visuo-semantic queries, combining the semantic facts extracted from the external resources and the similarity relations of the images. This paper presents a new web interface to browse and explore the dataset of IMGPEDIA in a more friendly manner, as well as new visuo-semantic queries that can be answered using 6 million recently added links from IMGPEDIA to WIKIDATA. We also discuss future directions we foresee for the IMGPEDIA project.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | Ferrada, Sebastian | Hombre |
Universidad de Chile - Chile
|
| 2 | Bravo, Nicolás | Hombre |
Universidad de Chile - Chile
|
| 3 | BUSTOS-CARDENAS, BENJAMIN EUGENIO | Hombre |
Universidad de Chile - Chile
|
| 4 | Hogan, Aidan | Hombre |
Universidad de Chile - Chile
|
| 5 | ACM | Corporación |
| Fuente |
|---|
| FONDECYT |
| CONICYT-PFCHA |
| Fondo Nacional de Desarrollo Científico y Tecnológico |
| Millennium Institute for the Foundations of Data |
| Agradecimiento |
|---|
| This work was supported by the Millennium Institute for the Foundations of Data, by CONICYT-PFCHA 2017-21170616 and by Fondecyt Grant No. 1181896. We would like to thank Larry Gonzalez and Camila Faundez for their assistance. |
| Acknowledgements. This work was supported by the Millennium Institute for the Foundations of Data, by CONICYT-PFCHA 2017-21170616 and by Fondecyt Grant No. 1181896. We would like to thank Larry González and Camila Faúndez for their assistance. |