The definition of ontologies within the multimedia domain still remains a challenging task, due to the complexity of multimedia data and the related knowledge. In this paper, we present a novel framework (MOWIS) aiming at realizing a system for building Multimedia Ontologies from Web Information Sources that has been realized within the PRIN 2007-2009 project Cooperare and presented in previous works. In particular, we propose: i) a multimedia ontology model that combines both low level descriptors and high level semantic concepts; ii) automatic construction of ontologies using the FLICKR web services that provide images, tags, keywords and sometimes useful annotation describing both the image content and personal interesting information. Eventually, we describe an example of automatic ontology generation in a specific domain and present some preliminary experimental results
A framework for Building Multimedia Ontologies from Web Information Sources / Chianese, Angelo; Moscato, Vincenzo; F., Persia; Picariello, Antonio; Sansone, Carlo. - (2012), pp. 83-90. (Intervento presentato al convegno 20th Italian Symposium on Advanced Database Systems (SEBD 12) tenutosi a Venezia, Italy nel June 24-27, 2012).
A framework for Building Multimedia Ontologies from Web Information Sources
CHIANESE, ANGELO;MOSCATO, VINCENZO;PICARIELLO, ANTONIO;SANSONE, CARLO
2012
Abstract
The definition of ontologies within the multimedia domain still remains a challenging task, due to the complexity of multimedia data and the related knowledge. In this paper, we present a novel framework (MOWIS) aiming at realizing a system for building Multimedia Ontologies from Web Information Sources that has been realized within the PRIN 2007-2009 project Cooperare and presented in previous works. In particular, we propose: i) a multimedia ontology model that combines both low level descriptors and high level semantic concepts; ii) automatic construction of ontologies using the FLICKR web services that provide images, tags, keywords and sometimes useful annotation describing both the image content and personal interesting information. Eventually, we describe an example of automatic ontology generation in a specific domain and present some preliminary experimental resultsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
