Developing HEO human emotions ontology
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Towards an RDF encoding of ConceptNet
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Sentic Computing: Techniques, Tools, and Applications
Sentic Computing: Techniques, Tools, and Applications
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With the advent of Web 2.0, tagging has become a common practice over the Web and a valuable source of metadata that has been increasingly exploited for resource classification and retrieval. Several research efforts have been conducted in the recent years to improve the productivity of user created tags by providing them with a proper structure and semantics. Also several approaches have been proposed to add implicit tags to resources both by analyzing the media and measuring the physiological and physical signals produced by the humans interacting with the media. This paper discusses the application of Semantic Web technologies to foster Affective Tagging. In particular, a human emotion ontology is proposed to standardize the main emotion models and map together different representations. In addition, public knowledge bases exposed as Linked Data can be exploited not only to disambiguate words and concepts, overcoming some of the main issues related to the use of natural language, but also to reveal the affective valence of such tags.