Semantic Image Retrieval Model for Sharing Experiences in Social Networks

Increasing numbers of people use social networks for keeping consistent contact with social life and acquaintances; sharing experiences became one of the most important requirement driving social networks. Users mostly use the media gathered during events, while sharing them socially. In this paper, we propose a semantic based model that involves several domain-based shared ontologies and use them to investigate image relationships among experiences. The proposed model is called Semantic Image Retrieval Model (SIRM) for sharing knowledge in social networks. In addition, we concentrate on a “Visit to zoo” scenario as a case study to show suitability and usability of the ontology based model for meeting requirements of sharing experiences among users of a social network. SIRM can also be used for different environments and scenarios in order to share experiences in a social network, build a knowledge-base of annotated media gathered during experiences by the people who visited the same site, or simply store the gathered media intelligently for future reference.